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We have listed some of the top data science seminar topics for final-year students. These seminars introduce new trends, tools, and real-world applications, making learning more engaging. 

Data science seminars can help students improve their resumes, develop essential technical skills, and explore career opportunities. 

What is a Data Science seminar?

A data science seminar is an educational event where experts teach students about data science concepts, tools, and real-world applications. These seminars cover topics like machine learning, data analysis, artificial intelligence, and big data. Trainers explain how businesses and researchers use data to make better decisions. 

Some seminars include hands-on workshops where students can practice coding and data visualization. Attending a data science seminar helps students learn new skills, explore career opportunities, and stay updated on the latest trends in technology.

Here are the Best Seminar Topics for Data Science

1. Assessment of Exploratory Data Analysis 

Technicality Level: Beginner

Description: Exploratory Data Analysis (EDA) helps understand datasets before applying models. It finds patterns, missing values, and outliers using visualizations and statistics. 

This seminar teaches students how to clean data, detect errors, and summarize key insights. Learning EDA improves decision-making and ensures better predictions in machine learning.

What to Cover in This Seminar Topic:

• Importance of EDA in data science
• Common techniques (summary statistics, visualizations)
• Handling missing values and outliers
• Identifying patterns and correlations
• Tools like Pandas, Matplotlib, and Seaborn

Learning Resources/Project References:

• Exploratory Data Analysis 

2. Big Data Analytics: Telecommunication Approach 

Technicality level: Intermediate

Description: Big data analytics helps telecom companies process and analyze massive amounts of customer data, network usage, and call records. It improves network efficiency, detects fraud, and enhances customer experience. 

Telecom providers use machine learning and AI to predict service issues, optimize bandwidth, and personalize offers. This seminar will explore how big data tools handle real-time and historical telecom data to drive better decisions.

What to cover in this seminar topic:

• Introduction to big data in telecom
• Data sources: call records, network logs, customer data
• Tools: Hadoop, Spark, and machine learning models
• Fraud detection and customer churn prediction
• Real-time data processing in telecom networks

Learning resources/project references:

• Big Data Analytics for Telecom 

3. Credit Card Fraud Detection 

Technicality level: Intermediate

Description: Fraudulent credit card transactions cause financial losses and security risks. This seminar explores how data science detects fraud using machine learning. Banks analyze transaction patterns to identify suspicious activity. 

Algorithms learn from past fraud cases to recognize new threats. This seminar explains how fraud detection models work, their challenges, and how to improve accuracy.

What to cover in this seminar topic:

• Introduction to credit card fraud and its impact
• Basics of fraud detection techniques
• Machine learning models for fraud detection
• Challenges in detecting fraud
• Best practices for building fraud detection systems

Learning resources/project references:

• Credit Card Fraud Detection Using Machine Learning Algorithms 

4. Online Detection Published Fake News

Technicality level: Beginner

Description: This seminar explores how to identify fake news online using data science. Participants will learn simple methods to spot false information on the internet.

What to cover in this seminar topic:

• Understanding what fake news is
• Recognizing the impact of fake news on society
• Learning basic techniques to detect fake news
• Exploring real-world examples of fake news detection

Learning resources/project references for this seminar:

• Fake News Detection project 

5. Analysis of customer segmentation 

Technicality Level: Beginner

Description: Businesses group customers based on their behavior, preferences, and demographics to improve marketing and sales. 

This process, called customer segmentation, helps companies target the right audience with personalized offers. Data scientists use clustering techniques like K-Means or DBSCAN to find patterns in customer data. 

In this seminar, students will learn how to segment customers using real-world datasets.

What to Cover in This Seminar Topic:

• Introduction to customer segmentation
• Importance of segmentation in marketing and business
• Common segmentation methods (demographic, behavioral, etc.)
• Basics of clustering algorithms (K-Means, DBSCAN)
• Hands-on data analysis with Python

Learning Resources/Project References:

• Customer Segmentation Analysis 

6. Cloud computing for data science 

Technicality level: Advanced

Description: Cloud computing helps data scientists store, process, and analyze large datasets without needing powerful local computers. It provides remote servers, storage, and tools that make data analysis faster and more efficient. 

This seminar explains how cloud platforms like AWS, Google Cloud, and Azure support data science workflows. You will learn how to use cloud-based tools for machine learning, big data processing, and model deployment.

What to cover in this seminar topic:

• Basics of cloud computing and its benefits for data science
• Popular cloud platforms (AWS, Google Cloud, Azure)
• Cloud-based data storage and databases
• Running machine learning models on the cloud
• Deploying data science applications using cloud services

Learning resources/project references:

• Cloud Computing Predict
• Integrating Data Science with Cloud Computing: Opportunities and Challenges

7. Sentiment analysis on Twitter data 

Technicality level: Beginner

Description: This seminar explores how to analyze tweets to understand people’s emotions about a topic. It introduces sentiment analysis, a technique that uses Natural Language Processing (NLP) and machine learning to classify tweets as positive, negative, or neutral. 

Students will learn how to clean Twitter data, use pre-trained models, and visualize sentiment trends.

What to cover in this seminar topic:

• Basics of sentiment analysis and NLP
• Collecting Twitter data using APIs
• Preprocessing tweets (removing noise, tokenization)
• Using machine learning models for sentiment classification
• Visualizing sentiment trends with graphs

Learning resources/project references:

• Sentiment Analysis of Twitter Data
• Twitter Sentiment Analysis 

8. Handwritten digit recognition 

Technicality level: Beginner

Description: Handwritten digit recognition is a machine-learning task where computers learn to read and identify numbers written by hand. 

It uses image processing and deep learning techniques to recognize digits from scanned documents or photos. This technology powers applications like automatic form reading and postal code recognition.

What to cover in this seminar topic:

• Basics of image processing
• Introduction to neural networks
• Understanding the MNIST dataset
• Building a simple digit recognition model using Python
• Training and testing the accuracy of models

Learning resources/project references:

• MNIST Handwritten Digit Classifier

9. Image caption generator 

Technicality Level: Intermediate

Description: An image caption generator is a machine-learning model that automatically creates short image descriptions. It uses deep learning techniques like Convolutional Neural Networks (CNNs) for image feature extraction and Recurrent Neural Networks (RNNs) or Transformers for text generation. 

This seminar will explain how AI can understand images and generate relevant captions, like humans describing pictures.

What to Cover in This Seminar Topic:

• Introduction to image captioning
• Role of CNNs and RNNs in caption generation
• Using pre-trained models like VGG16 and LSTM
• Implementation using TensorFlow/Keras
• Datasets like MS COCO for training
• Real-world applications and challenges

Learning Resources/Project References:

• Image Caption Generator

10. Personalised healthcare recommendation system

Technicality Level: Intermediate

Description: This seminar explores how machine learning helps doctors and patients get personalized health advice. 

A personalized healthcare recommendation system analyzes medical history, lifestyle, and symptoms to suggest treatments, diet plans, or medications. It uses AI to provide tailored recommendations, making healthcare more effective.

What to Cover in This Seminar Topic:

• Basics of recommendation systems
• Machine learning models for healthcare recommendations
• Data collection and preprocessing
• Ethics and privacy concerns in medical AI
• Real-world applications and case studies

Learning Resources/Project References:

• Personalized Healthcare Recommendations System

11. Airbnb price prediction 

Technicality level: Intermediate

Description: This seminar explores how to predict Airbnb rental prices using data science. Participants will learn how to collect and analyze property data, identify key pricing factors, and build machine-learning models. 

Students can estimate rental prices based on location, amenities, and demand by understanding these concepts.

What to cover in this seminar topic:

• Introduction to Airbnb dataset
• Data cleaning and preprocessing
• Feature selection and engineering
• Applying machine learning models (Linear Regression, Random Forest, etc.)
• Evaluating model performance
• Visualizing insights from data

Learning resources/project references:

• AirBnB Price Prediction

12. Resume screening system 

Technicality level: Advanced 

Description: This seminar explores how companies use machine learning to filter job applications. A resume screening system scans resumes, picks relevant skills, and ranks candidates based on job requirements. 

It saves recruiters time and ensures fair selection. Attendees will learn how to build an automated system using Natural Language Processing (NLP) and classification models.

What to cover in this seminar topic:

• Importance of automated resume screening
• How NLP extracts skills, experience, and education
• Training machine learning models for classification
• Challenges like bias in AI and overcoming them
• Hands-on implementation with Python

Learning resources/project references:

• Automated Resume Screening System (With Dataset)

13. Data mining in search engine analytics

Technicality level: Advanced 

Description:
Search engines process massive amounts of data to show relevant results. Data mining helps analyze search queries, user behavior, and ranking factors. This seminar explores how search engines use algorithms to improve accuracy and personalization. 

Students will learn about techniques like web scraping, keyword analysis, and trend prediction.

What to cover in this seminar topic:

• Basics of search engines and data mining
• Web crawling and indexing
• User behavior analysis using data mining
• Keyword trend prediction and ranking factors
• Sentiment analysis in search queries

Learning resources/project references:

• Search engine optimisation using a data mining approach 

14. Generative AI- Gen AI

Technicality level: Beginner

Description: Generative AI (Gen AI) helps computers create new content like text, images, music, or videos. It learns from existing data and generates original outputs based on patterns. 

This technology powers chatbots, AI art, and even deepfake videos. Companies use it for product design, marketing, and creative work. The seminar will explain how Gen AI works and its impact on different industries.

What to cover in this seminar topic:

• Basics of AI and machine learning
• How generative models work (e.g., GPT, DALL·E)
• Applications in real-world scenarios
• Ethical concerns and limitations

Learning resources/project references:

• Awesome Generative AI

15. Time series forecasting on weather data

Technicality Level: Intermediate

Description: This seminar explores how to predict future weather conditions using past data. Time series forecasting helps analyze temperature, rainfall, and wind speed patterns. 

It uses mathematical models and machine learning to make accurate weather predictions. Understanding these techniques can improve climate research and disaster preparedness.

What to Cover in This Seminar Topic:

• Basics of time series forecasting
• Weather data collection and preprocessing
• Common forecasting models (ARIMA, LSTM, Prophet)
• Model evaluation techniques
• Real-world applications in weather prediction

Learning Resources/Project References:

• Weather Forecasting: Using Time Series Analysis Under Different Stations Of The UK
• Deep Neural Network for Weather Time Series Forecasting

Thinking about a data science career but not sure where to start? We’ve all been there.

Let’s walk through the basics of launching your Data Science career.

Bonus: Other seminar and research topics for Data Science

1. Understanding Bias in Machine Learning Models

Bias in machine learning happens when a model makes unfair decisions based on incorrect patterns in data. It can lead to discrimination and inaccurate predictions.

This seminar covers different types of bias, such as selection bias and confirmation bias. Students will learn how biased data affects AI decisions and ways to reduce bias in machine learning models.

2. The Intersection of Data Science and Cybersecurity

Data science helps detect cyber threats, while cybersecurity protects data from attacks. Together, they make systems safer.

This seminar explores how machine learning detects fraud, stops cyberattacks, and strengthens online security. Students will see real-world examples of AI-powered cybersecurity tools.

3. Data Science Skill Gap Analysis

A skill gap happens when companies need certain skills but workers don’t have them. In data science, this gap slows down progress.

This seminar explains what skills data scientists need and why some skills are missing. Students will explore ways to bridge the gap through training and education.

4. Data Quality Management

Bad data leads to bad decisions. Data quality management ensures that data is clean, complete, and useful.

In this seminar, students will learn how to check data accuracy, remove errors, and improve data quality. They will also understand why good data is important for AI and business.

5. Analysis of Forest Fire Prediction

Forest fires destroy land, wildlife, and homes. Data science can help predict where fires may happen.

This seminar teaches students how data scientists use temperature, wind, and humidity data to predict fires. They will also learn about AI tools that help firefighters react faster.

6. Analysis of Gender Detection and Age Prediction

AI can estimate a person’s age and gender using images, voice, and text. This technology is used in security, marketing, and social media.

Students will explore how machine learning analyzes faces and voices to make predictions. They will also learn about challenges such as fairness and accuracy.

7. Smart Sustainable Mobility and Communities

Smart cities use data to improve transportation and make life better. Sustainable mobility means using eco-friendly ways to travel.

This seminar shows students how data science helps in smart traffic management, electric vehicles, and pollution control. They will also explore smart city projects around the world.

8. Sustainable Development

Sustainable development means using resources wisely to protect the future. Data science helps track climate change, pollution, and resource use.

Students will learn how AI predicts environmental changes and helps in making green policies. They will also see how data science supports clean energy projects.

9. Technology Behind the AI Revolution

AI is changing the world by making machines smarter. But what makes AI work?

This seminar explains the key technologies behind AI, such as deep learning, neural networks, and big data. Students will understand how these technologies power chatbots, self-driving cars, and more.

10. High-Performance Computing: Big is Beautiful

High-performance computing (HPC) solves complex problems by using powerful computers. It is used in weather prediction, AI, and space exploration.

Students will discover how supercomputers process massive amounts of data quickly. They will also see why HPC is important for science and technology.

11. Data Engineering: The Unglamorous Reality Behind Data Science

Data engineers prepare raw data for analysis. Without them, data scientists cannot build AI models.

This seminar explains the hidden but important work of data engineers. Students will learn how to clean, store, and organize data to make it useful.

12. Velocity 360: A Tour on the 3rd Dimension of Big Data

Big data is not just large; it moves fast. Velocity is about how quickly data is created and processed.

Students will explore how real-time data powers live tracking, stock markets, and smart assistants. They will also learn why speed matters in data science.

13. Digital Humanities: Art is Not Only for Humans Anymore

AI is creating art, music, and literature. It is changing the way we think about creativity.

This seminar explores how AI analyzes history, writes poems, and creates paintings. Students will discuss whether AI can truly be creative.

14. Federated Learning: The Future of Edge Intelligence is Now!

Federated learning trains AI models without sharing data. It keeps data private while improving AI performance.

Students will learn how federated learning works in phones, hospitals, and businesses. They will also see why it is important for privacy and security.

15. Explainability and Governance of Artificial Intelligence

AI makes many decisions, but can we trust them? Explainability means understanding how AI makes choices.

This seminar teaches students how AI transparency improves fairness and trust. They will also explore rules and laws that make AI responsible.

Further reading: Data science interview questions

How 10Pie helps you in preparing for your next Data Science seminar presentation

10Pie helps you prepare for your data science seminar presentation with the right resources. You can learn key topics and understand important terms with simple explanations. 

Our technology glossary gives clear definitions of complex ideas. At 10Pie, you will find multiple career guides, including the Data Science Career Guide, which helps you stay updated on industry trends. 

You will find useful insights and real-world examples from these guides that will help you do better and create well-informed seminar presentations. 

Somrita Shyam

Somrita Shyam is a content writer with 4.5+ years of experience writing blogs, articles, web content, and landing pages in multiple domains. She holds a master’s degree in Computer Application (MCA) and is a Gold Award winner at Vidyasagar University. Her knowledge of the tech industry and experience in crafting creative content helps her write simple and easy-to-understand tech pieces for readers of all ages. Her interest in content writing began after helping PhD scholars in submitting their assignments. Later in 2019, she started working as a freelance content writer at Write Turn Services, and has worked with numerous clients, before joining Experlu (An UK based accounting firm) in 2022 and working as a full-time content writer in GigDe (2022-2023).

www.linkedin.com/in/somrita-s-6aa595134/

Whether you’re interested in AI, business intelligence, or sustainability, we have listed the top Data Analytics seminar topics that will help you develop key analytical skills.

What is a data analytics seminar?

A data analyst seminar is an event where experts teach people how to analyze data. Students can learn how to collect, organize, and study data to find useful patterns. It also shows how businesses use data to make better decisions. 

Students learn about tools like Excel, SQL, and Python from a data analytics seminar. Some seminars include hands-on activities or real-world examples for a better understanding of different data analytics concepts. These events help beginners and professionals improve their skills.

Many people confuse data science and business analytics. Knowing the core distinctions between data science and business analytics is a necessity for anyone in the data analytics sphere.

Best Seminar Topics for Data Analytics 

1. AI-powered Data Analytics 

Technicality level: Intermediate level

Description: This seminar explores how artificial intelligence (AI) improves data analysis. AI helps process large amounts of data quickly and finds patterns that humans might miss. 

Machine learning models make predictions based on past data, helping businesses make better decisions. Students will learn how AI-powered tools simplify data analytics, automate tasks, and provide accurate insights.

What to cover in this seminar topic:

• Basics of AI in data analytics
• How machine learning improves data insights
• Popular AI-powered analytics tools
• Real-world applications in business and healthcare
• Hands-on demo using AI models

Learning resources/project references:

• AnalytiBot

2. Data Storytelling and Visualization 

Technicality level: Beginner

Description: Data storytelling turns numbers into meaningful insights. It combines visuals and narratives to help people understand complex data easily. 

This seminar teaches you how to create clear and engaging charts, graphs, and dashboards. Students will learn how to turn raw data into a story that informs and influences decisions.

What to cover in this seminar topic:

• Basics of data visualization (charts, graphs, dashboards)
• Importance of storytelling in data analysis
• Choosing the right visualization for different datasets
• Common mistakes and best practices in visualization
• Introduction to tools like Tableau, Power BI, and Matplotlib

Learning resources/project references:

• Data Storytelling
• Data storytelling with Python

3. Quantum computing and Data analytics

Technicality Level: Intermediate

Description: Quantum computing processes data in a way that is much faster than regular computers. It uses quantum bits (qubits) that can perform multiple calculations at once. 

In data analytics, this means solving complex problems faster, analyzing huge datasets efficiently, and improving machine learning models. This seminar will introduce you to how quantum computing can change data analytics and where it is being used today.

What to cover in this seminar topic:

• Basics of quantum computing (qubits, superposition, entanglement)
• Differences between classical and quantum computing in data analytics
• Real-world applications in data science and big data
• Challenges and future potential

Learning resources/project references:

• Awesome Quantum Computing

4. Reducing manufacturing failures

Technicality Level: Beginner

Description: This seminar explains to students how factories can reduce product defects and machine breakdowns. It covers simple ways to track errors, find their causes, and fix them using data. 

Students will learn how sensors, reports, and basic data tools help improve quality and reduce waste in manufacturing.

What to Cover in This Seminar:

• Common causes of manufacturing failures
• Importance of collecting and analyzing production data
• Role of sensors and real-time monitoring in quality control
• How predictive analytics helps prevent machine breakdowns
• Simple data visualization techniques for error tracking

Learning Resources/Project References:

• Reducing Manufacturing Failures

5. Market Basket Analysis

Technicality level: Advanced

Description: Market Basket Analysis utilizes complex algorithms to analyze extensive transactional data, uncovering intricate relationships between products. 

This analysis enables businesses to predict future purchasing trends, personalize marketing strategies, and enhance cross-selling opportunities. Students can learn about it in depth from this seminar.

What to cover in this seminar topic:

• In-depth exploration of advanced algorithms beyond Apriori, such as FP-Growth
• Techniques for handling large-scale data and improving computational efficiency
• Integration of Market Basket Analysis with machine learning models for predictive analytics
• Discussion on challenges like dealing with sparse data and dynamic inventory
• Exploration of high-utility itemset mining

Learning resources/project references for this seminar:

• Market Basket Analysis of Store Data

6. City Employee Salary Data Analysis

Technicality level: Beginner Level

Description: This seminar explores how to analyze city employee salary data using data analytics techniques. Students will learn how to clean, visualize, and interpret salary trends across different job roles and departments. 

It introduces basic concepts like data collection, preprocessing, and simple statistical analysis to find insights.

What to cover in this seminar topic:

• Understanding city employee salary datasets
• Data cleaning and preprocessing techniques
• Exploring salary trends using visualizations
• Identifying salary disparities across job roles
• Basic statistical methods for salary analysis

Learning resources/project references:

• Employee Data Analysis

7. Data analysis and visualisation using Apache Spark and Zeppelin 

Technicality level: Beginner/Intermediate

Description: Students will learn how to analyze and visualize big data using Apache Spark and Zeppelin. Apache Spark processes large datasets quickly, while Zeppelin provides an interactive environment to write and run code. 

This seminar covers how to clean data, perform analysis, and create visual reports. By the end, students will understand how to use these tools to make data-driven decisions.

What to cover in this seminar topic:

• Basics of Apache Spark and Zeppelin
• Setting up Spark with Zeppelin
• Data preprocessing and cleaning
• Running queries and transformations
• Creating interactive visualizations

Learning resources/project references:

• Data Analytics using Apache Zeppelin and Spark

8. Analysing Co2 Emissions 

Technicality level: Advanced

Description: This seminar explores machine learning techniques to predict future CO₂ emissions. Participants will build predictive models using regression analysis and neural networks. 

They will work with large-scale climate data and apply AI-driven approaches to identify key emission drivers. The goal is to understand how technology can help in making data-driven environmental policies.

What to cover in this seminar topic:

• Collecting and processing real-time CO₂ data
• Feature engineering for predictive modeling
• Machine learning models (Linear Regression, Random Forest, Neural Networks)
• Evaluating model accuracy and optimization techniques
• Applying AI in sustainability and policy-making

Learning resources/project references:

• Co2 Emission Prediction 

9. Data Analysis using clustering 

Technicality level: Advanced

Description: Clustering involves grouping data points into subsets where members share similar properties. Advanced clustering techniques address complex datasets with varying densities and noise. 

Methods like DBSCAN (Density-Based Spatial Clustering of Applications with Noise) can identify clusters of arbitrary shape and handle outliers effectively.

What to cover in this seminar topic:

• In-depth study of advanced clustering algorithms such as DBSCAN and Gaussian Mixture Models
• Handling high-dimensional data and the curse of dimensionality in clustering
• Techniques for clustering large-scale datasets
• Incorporating domain knowledge into clustering processes
• Case studies showcasing the application of advanced clustering in various industries

Learning resources/project references for this seminar:

• Cluster analysis 
• raimujicac/Data-Mining-Projects – GitHub

10. Data Analytics in Smart Cities

Technicality Level: Advanced 

Description: Smart cities use data to improve daily life. Sensors, cameras, and devices collect information about traffic, pollution, and energy use. Data analysts study this information to find patterns and suggest better ways to manage resources. 

This seminar explains how data analytics helps in solving urban challenges like reducing traffic jams, saving energy, and making cities safer.

What to Cover in This Seminar Topic:

• Basics of smart cities and IoT devices
• How data is collected from urban systems
• Analyzing city data to improve transportation and energy use
• Case studies of data-driven smart city projects
• Tools and techniques used in smart city analytics

Learning Resources/Project References:

• Smart City Analytics 

11. Movies Review Scraping and Analysis 

Technicality level: Beginner/Intermediate

Description: This seminar covers how to collect and analyze movie reviews from websites like IMDb or Rotten Tomatoes. Students will learn to scrape review data, clean it, and find insights using Python. 

They will also explore sentiment analysis to understand audience opinions. The session includes practical coding examples and data visualization techniques.

What to cover in this seminar topic:

• Web scraping basics with Python (BeautifulSoup, Scrapy)
• Extracting movie reviews from websites
• Cleaning and processing text data
• Sentiment analysis using Natural Language Processing (NLP)
• Visualizing trends in movie reviews

Learning resources/project references:

• IMDB web scraping and sentiment analysis 

12. Zomato Data Analysis Using Python 

Technicality level: Intermediate

Description: This seminar explores how to analyze Zomato restaurant data using Python. Attendees will learn how to clean, visualize, and interpret data to uncover trends in restaurant ratings, cuisines, and pricing. Python libraries like Pandas, Matplotlib, and Seaborn will be used for data manipulation and visualization. 

This seminar will also introduce basic machine learning techniques to predict ratings and customer preferences.

What to cover in this seminar topic:

• Introduction to Zomato dataset
• Data cleaning and preprocessing using Pandas
• Data visualization with Matplotlib and Seaborn
• Exploratory data analysis (EDA) on restaurant ratings and cuisine trends
• Building a simple predictive model using Scikit-learn

Learning resources/project references:

• Zomato Data Analysis Python 

13. ESG Analytics: Measuring Sustainability in Business 

Technicality Level: Intermediate

Description: ESG (Environmental, Social, and Governance) analytics helps businesses track their sustainability performance. Companies use data to measure their carbon footprint, social impact, and corporate ethics. 

This seminar will explore how organizations collect, analyze, and report ESG data to meet regulations and attract investors. Participants will learn about key ESG metrics, data sources, and visualization techniques. This seminar will teach you about ESG analytics and how it helps businesses improve transparency and decision-making.

What to Cover in This Seminar Topic:

• Introduction to ESG and its importance
• Data sources for ESG analytics
• Measuring environmental impact (carbon emissions, energy use)
• Assessing social responsibility (labor rights, diversity, community impact)
• Governance factors (ethics, leadership, compliance)
• Tools and techniques for ESG data analysis
• ESG reporting frameworks (GRI, SASB, TCFD)

Learning Resources/Project References:

• ESG Score Prediction from Sustainability Reports

14. Sports Analytics: Data-Driven Performance Optimisation 

Technicality Level: Intermediate

Description: This seminar teaches students about how data helps improve athlete performance and team strategies. Coaches and analysts use data from games, player movements, and fitness levels to make better decisions. 

With machine learning and statistical models, they predict injuries, analyze opponents, and enhance training plans. Sports organizations use these insights to gain a competitive edge.

What to Cover in This Seminar Topic:

• Basics of sports data collection
• Key metrics in player and team performance
• Role of machine learning in sports predictions
• Injury prevention using data analytics
• Case studies of teams using analytics successfully

Learning Resources/Project References:

• Awesome Sports Analytics 

15. Data Analytics in Business Making 

Technicality Level: Beginner

Description: Businesses use data analytics to make smart decisions. It helps companies understand customers, predict trends, and improve products. 

This seminar explains how data is collected, analyzed, and used to solve business problems. You will see real-world examples of companies using data to grow.

What to cover in this seminar topic:

• Importance of data in business
• Basics of data collection and analysis
• Common business analytics tools (Excel, SQL, Power BI)
• Case studies of data-driven decisions

Learning resources/project references:

• Musc Store Analysis

Bonus: Other seminar and research topics for data analytics 

1. Building Job Portal using Twitter Data

A job portal helps people find jobs. This seminar will show how to collect and analyze job-related tweets to create a simple job portal.

Students will learn how to find job postings on Twitter using keywords and hashtags. They will clean and organize the data, then build a system to match job seekers with job openings.

2. Event Data Analysis

Events like concerts, sports matches, and conferences create lots of data. This seminar will teach how to collect and study event data to find patterns.

Students will learn how to analyze ticket sales, attendance, and social media reactions. They will discover how data can help improve future events.

3. Building Music Recommendation Engine

A music recommendation engine suggests songs based on listening history. This seminar will explore how data helps predict what songs people might like.

Students will learn how streaming platforms use data to recommend songs. They will work with user preferences, song features, and machine learning to build a basic recommendation system.

4. Housing Price Analysis and Predictions

House prices change based on location, size, and market trends. This seminar will show how to analyze and predict housing prices using data.

Students will learn how to collect real estate data, find price trends, and build models that estimate future house prices. They will understand how data helps buyers and sellers make smart choices.

5. Customer Churn Analysis

Businesses lose customers over time. This seminar will explore how data helps predict when and why customers leave.

Students will learn to analyze customer behavior and find patterns in shopping habits. They will build models that help businesses keep customers happy and loyal.

6. HR Analytics to Track Employee Performance

Companies use data to measure employee performance. This seminar will explain how HR teams use analytics to improve workplace productivity.

Students will learn how to analyze attendance, work quality, and job satisfaction. They will explore ways data can help employees grow and succeed.

7. Google Search Analysis

Every Google search creates data. This seminar will show how analyzing search trends can reveal popular topics and user interests.

Students will learn how to collect and study research data. They will explore how businesses and researchers use search trends to make decisions.

8. Anomaly Detection in Time Series Data

Anomalies are unexpected changes in data. This seminar will focus on how to find unusual patterns in time-based data.

Students will learn how to detect fraud, sensor failures, and stock market crashes. They will use simple tools to spot unusual trends in real-world data.

9. Food Price Forecasting

Food prices go up and down based on supply, demand, and weather. This seminar will teach how to predict food price changes using data.

Students will collect past price data, find patterns, and build models to forecast future food costs. They will understand how data helps farmers, stores, and consumers plan better.

10. Word Frequency in Classic Novels

Writers use certain words more than others. This seminar will explore how to count and compare word usage in famous books.

Students will analyze novels to find the most common words and themes. They will learn how data can help in literature studies.

11. Modelling Car Insurance Claim Outcomes

Car insurance companies use data to predict claims. This seminar will explain how data helps them decide costs and risks.

Students will analyze past claims to find patterns. They will build models that estimate the chances of accidents and insurance payouts.

12. Analyse International Debt Statistics

Countries borrow money to grow their economies. This seminar will explore how to analyze debt statistics from different nations.

Students will study how much countries owe, to whom, and why. They will learn how data helps governments and organizations make financial decisions.

13. Monitoring Financial Fraud Detection Model

Banks use data to catch fraud. This seminar will show how data analytics helps detect fake transactions.

Students will learn how fraud happens and how data models identify suspicious activities. They will explore real-world fraud cases and prevention techniques.

14. Data Ethics and Privacy

Data collection raises privacy concerns. This seminar will explain the importance of handling data responsibly.

Students will learn about data security, personal privacy, and ethical data use. They will explore real cases where data misuse caused problems.

15. Augmented Analytics and Automation

Augmented analytics uses AI to speed up data analysis. This seminar will show how automation helps businesses make quick decisions.

Students will explore AI-driven data tools and learn how they save time in this seminar. They will understand how automation makes data analysis easier and more efficient.

How 10Pie helps you in preparing for your next data analytics seminar presentation

Preparing for a data analytics seminar can feel overwhelming, but 10Pie makes it easier for you. Our technology glossary helps you understand key analytics terms in simple words. You can explore career paths in data analytics to see how professionals use data in real life. 

Need to improve your skills? 

Check out our data analyst, data science, and Power BI courses. Plus, our blog keeps you updated on the latest trends. With 10Pie, you’ll feel confident and ready to present!

Somrita Shyam

Somrita Shyam is a content writer with 4.5+ years of experience writing blogs, articles, web content, and landing pages in multiple domains. She holds a master’s degree in Computer Application (MCA) and is a Gold Award winner at Vidyasagar University. Her knowledge of the tech industry and experience in crafting creative content helps her write simple and easy-to-understand tech pieces for readers of all ages. Her interest in content writing began after helping PhD scholars in submitting their assignments. Later in 2019, she started working as a freelance content writer at Write Turn Services, and has worked with numerous clients, before joining Experlu (An UK based accounting firm) in 2022 and working as a full-time content writer in GigDe (2022-2023).

www.linkedin.com/in/somrita-s-6aa595134/

This curriculum outlines essential topics from programming and data analysis to machine learning and advanced applications, preparing students for success in the field.

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Data Science course syllabus and curriculum

Here’s a Data Science course syllabus at a glance:

Module 1: Data Science Foundations

• Importance of data in decision-making
• The Data Science Lifecycle (problem definition, data collection, preprocessing, EDA, feature engineering, model building and evaluation, deployment, and monitoring)

Hands-on projects to practice: 

• Traffic Pattern Analysis: Optimize traffic flow and reduce congestion using traffic data.
• Predicting House Prices: Predict house prices based on features like the number of bedrooms, bathrooms, and location.
• Weather Forecasting: Analyze weather data to predict weather patterns and temperatures.

Module 2: Python for Data Science

Python Libraries and Frameworks

• NumPy for numerical computing
• Pandas for data manipulation and analysis
• Matplotlib and Seaborn for data visualization
• Scikit-learn for machine learning

Advanced Python Concepts

• List comprehensions and generator expressions
• Functional programming (lambda, map, filter, reduce)
• Object-oriented programming principles
• Decorators and context managers

Hands-on projects to practice: 

• COVID-19 Data Visualization: Load a dataset of COVID-19 cases using Matplotlib and Seaborn to create informative and attractive visualizations(line plots, bar charts, and heatmaps).
• Spam Classification: Train a Scikit-learn model to classify emails as spam or not spam.
• Web Scraper: Use list comprehensions and generator expressions to build a web scraper that extracts data from a website.
• Machine Learning Model Deployment: Use Scikit-learn and Flask to deploy a machine learning model as a web application.

Module 3: Statistical Inference and Modeling

Probability Distributions

• Discrete distributions (Bernoulli, Binomial, Poisson)
• Continuous distributions (Normal, Exponential, Gamma)
• Joint and conditional probability

Hypothesis Testing

• One-sample and two-sample tests
• ANOVA and Chi-square tests
• Non-parametric tests

Regression Analysis

• Linear regression (simple and multiple)
• Logistic regression for classification
• Regularization techniques (Ridge, Lasso, Elastic Net)

Hands-on projects to practice: 

• Coin Flip Simulation: Simulate 10,000 coin flips and calculate the probability of getting a certain number of heads.
• Website Conversion Rate: Use a one-sample t-test to determine if a website’s conversion rate is significantly different from an industry benchmark.
• Energy Consumption Prediction: Use simple linear regression to predict energy consumption based on a single feature (e.g., number of occupants).
• Credit Risk Assessment: Use logistic regression to predict the probability of a customer defaulting on a loan based on credit information.

Module 4: Machine Learning Fundamentals

Supervised Learning

• Linear and logistic regression
• Decision trees and random forests
• Support Vector Machines (SVMs)
• Ensemble methods (bagging and boosting)

Unsupervised Learning

• K-means clustering
• Hierarchical clustering
• Principal Component Analysis (PCA)
• Anomaly detection techniques

Model Selection and Evaluation

• Train-validation-test split
• Cross-validation techniques
• Performance metrics (accuracy, precision, recall, F1-score)
• ROC curves and AUC

Hands-on projects to practice: 

• Credit Card Approval: Predict credit card approval based on credit score, income, and debt-to-income ratio using logistic regression.
• Wine Quality Prediction: Use ensemble methods (bagging and boosting) to predict wine quality based on features like chemical composition and sensory data.
• Gene Expression Analysis: Use hierarchical clustering to identify patterns in gene expression data.
• Titanic Survival Prediction: Predict Titanic passenger survival based on demographic and travel information.

Module 5: Deep Learning

Neural Network Architectures

• Feedforward neural networks
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Autoencoders and Generative Adversarial Networks (GANs)

Deep Learning Libraries and Frameworks

• TensorFlow and Keras
• PyTorch

Advanced Deep Learning Topics

• Transfer learning and fine-tuning
• Attention mechanisms
• Reinforcement learning
• Interpretability and explainability

Hands-on projects to practice: 

• Image Classification with CNNs: Build a CNN model to classify images into different categories (e.g., animals, vehicles, buildings) using the CIFAR-10 dataset.
• Sentiment Analysis with RNNs: Develop an RNN model to classify movie reviews as positive or negative using the IMDB dataset.
• Generative Adversarial Networks (GANs) for Face Generation: Build a GAN model to generate new face images using the CelebA dataset.
• Chatbot with Seq2Seq RNNs: Build a chatbot that responds to user queries using a sequence-to-sequence RNN model trained on the Cornell Movie Dialog Corpus.

Module 6: Natural Language Processing (NLP)

Text Preprocessing and Representation

• Tokenization and normalization
• Stemming and lemmatization
• Bag-of-words and TF-IDF
• Word embeddings (Word2Vec, GloVe, FastText)

NLP Applications

• Sentiment analysis (using lexicon-based and machine-learning approaches)
• Text classification (using Logistic Regression, SVM, and Deep Learning)
• Named Entity Recognition (NER) (using Conditional Random Fields (CRFs) and Deep Learning)
• Machine translation
• Text generation

NLP Libraries and Frameworks

• NLTK and spaCy
• Gensim for topic modeling
• Transformers for state-of-the-art NLP models

 Hands-on projects to practice: 

• Language Translation: Use the Transformers library to build a machine translation model to translate sentences from one language to another using the WMT dataset.
• Topic Tracker: Apply topic modeling using Gensim to extract underlying topics from a dataset of news articles.
• News Navigator: Implement a Named Entity Recognition (NER) model to extract named entities (e.g., people, organizations, locations) from news articles.
• Word Wizard: Use Word2Vec, GloVe, and FastText to create word embeddings and calculate text similarity between sentences.

Module 7: Big Data and Distributed Computing

Big Data Ecosystem

• Hadoop (HDFS, MapReduce, Hive, Spark)
• Apache Spark, Spark Streaming, and Kafka
• NoSQL databases (MongoDB, Cassandra, HBase)

Spark Programming

• RDDs and DataFrames
• Spark SQL and Datasets
• Spark MLlib for machine learning
• Spark Streaming for real-time data processing

Scalable Machine Learning

• Distributed training and inference
• Hyperparameter tuning at scale
• Model serving and deployment

Hands-on projects to practice:

• Twitter Sentiment Analysis: Analyze Twitter tweets in real time using Spark Streaming, Spark MLlib, and MongoDB.
• Customer Purchase Prediction: Build a machine learning model using Spark MLlib to predict customer purchases based on transaction data.
• Scalable Recommendation System: Build a scalable recommendation system using Apache Spark, Spark MLlib, and TensorFlow Serving.

Module 8: Data Engineering and Pipelines

Data Ingestion and Extraction

• Batch and streaming data sources
• APIs and web scraping
• Data lakes and data warehouses

Data Transformation and Orchestration

• ETL pipelines with Apache Airflow
• Data transformation with Apache Beam
• Containerization and orchestration (Docker, Kubernetes)

Data Quality and Governance

• Data profiling and anomaly detection
• Data lineage and provenance
• Privacy and security considerations (laws like GDPR, CCPA, HIPAA)

Hands-on projects to practice:

• Weather Data Ingestion: Ingest weather data from APIs and web scraping using Apache Airflow, and load into a data warehouse using Apache Beam.
• Data Quality Guard: Create a data quality pipeline using Apache Airflow to detect anomalies and perform data profiling, with data lineage and provenance using Apache Atlas and Apache Beam.
• ETL Flow: Build a scalable ETL pipeline by packaging it with Docker and managing it with Kubernetes, using Apache Beam to move and prepare batch data (e.g., CSV files) for a PostgreSQL database.
• Privacy Shield: Implement data privacy and security considerations in a data pipeline using Apache Airflow and Apache Beam, with access control and encryption using Apache Ranger and Apache Knox.

B.Sc Data Science Syllabus

The BSc (Hons) in Data Science is a 3-year undergraduate (UG) program that provides students with a strong foundation in Data Science principles and practices.

The average fees for the BSc (Hons) in Cyber Security course range from INR 30,000 to 4,00,000 per annum, depending on the college and location.

B.Tech Data Science syllabus

The B.Tech in Data Science is a 4-year undergraduate program that equips students with the knowledge and skills to analyze and interpret complex data to make informed decisions. You must complete 12th grade with a minimum of 45-60% marks, including Mathematics.

Here is the B.Tech Data Science syllabus semester-wise.

 BCA Data Science syllabus

The BCA in Data Science is a 3-year undergraduate program that equips students with the knowledge and skills to analyze and interpret complex data to make informed decisions. You must complete your 12th grade with a minimum of 45-60% marks, including Mathematics.

• This course is designed to provide you with knowledge in both computer applications and data science, bridging the gap between the two fields. 

Here are some key details about the BCA Data Science program:

M.sc Data Science Syllabus

The M.Sc in Data Science is a 2-year program focused on advanced data analysis, machine learning, and big data technologies. 

Designed for graduates with a relevant background, the program typically requires 50-60% in a bachelor’s degree and may include entrance exams or interviews.

M.Tech Data Science Syllabus

The M.Tech in Data Science is a 2-year postgraduate program focused on advanced data analysis, machine learning, and big data technologies.

It’s designed for graduates with a relevant background and typically requires 50-60% in a bachelor’s degree, along with qualifying in entrance exams like GATE, followed by an interview.

Diploma Data Science Course Syllabus

The Diploma in Data Science is a comprehensive program designed to provide practical skills in data analysis, machine learning, and data management.

 Typically lasting 6 months to 1 year, it is suitable for those seeking a focused introduction to data science. 

Admission usually requires a basic understanding of mathematics and computer science, with entry based on academic qualifications or entrance tests.

Data Science course subjects and topics to learn

If you want to start a career in data science, below are the topics you need to learn:

• Programming (Python or R)
• Statistics and mathematics 
• Data wrangling, manipulation, and management 
• Data visualisation 
• Machine learning and deep learning 

1. Programming (Python or R)

Python and R are often a minimum requirement in entry-level data science roles. Python ranks first as a programming language as per TIOBE and PYPL Index. R is a top option for many data scientists for data manipulation, processing, and so on. 

Also, tech Giants like Google, Microsoft, and Netflix heavily rely on Python and R for data science tasks. 

Hence, learning these languages will increase your chances of employability, be it internships or placements. You can also learn SAS, SQL, or Julia.

2. Statistics and Mathematics 

As a data scientist, you should know how to collect, present, and interpret data. Therefore, you should learn different concepts like mean, median, mode, etc., in statistics. You must understand statistical techniques. 

You should also cover areas like calculus, linear algebra, matrices, probability, and other important mathematical concepts. 

This helps you write high-quality algorithms and machine-learning models.

3. Data wrangling, manipulation, and management

These topics help you work with raw, real-world data and perform complex queries. 

These tasks are foundational in data science as you must prepare the data to provide accurate business insights. Data wrangling deals with cleaning and organising data sets for easier analysis. 

You are also expected to learn database management to extract data and transform it into suitable formats. 

Data wrangling tools:

•  Altair 
• Alteryx 
• Talend 

Data manipulation tools:

• Pandas 
• NumPy
• scikit-learn 

Database management tools:

• MySQL
• MongoDB
• Oracle database 

4. Data visualisation 

Being able to present data is important to being a data scientist. You will need to master reporting and visualisation to present business insights to key stakeholders. So, learn how to create charts, graphs, dashboards, and tables.

 Learning the tools below will prepare you well in this area:

• Tableau 
• Power BI
• QlikView/Qlik Sense 
• Matplotlib 
• Plotly 

5. Machine learning and deep learning

As per Stanford University, machine learning is the most in-demand skill followed by NLP. With this skill, you can develop algorithms and models that make predictions and automate decision-making. 

Students who learn these techniques can solve real-world problems. These skills are highly sought-after in the job market. 

To begin, master the fundamentals of statistics and programming. Then, explore introductory courses on machine and deep learning.

Data Science Course Fees and Duration 2024

What is the course fee for Data Science courses?

The fees of a data science course typically start from INR 30,000 and can reach up to INR 3 lakhs. You can find various institutes that offer both online and offline data science courses. For instance, IIT Madras offers the following fee structure:

Another example: ExcelR in Hyderabad:

The course fees for data science vary on different factors:

1. Brand affiliation or partnerships with Microsoft, Google, NASSCOM, etc.
2. Opting for certification
3. Topics covered (advanced/foundational)
4. Learning Format (instructor-led, real-time support)
5. Job placement assistance 

To get a clearer picture, explore the types of data science jobs, including job responsibilities, and prerequisites, and the latest job statistics, and trends for 2024. Additionally, gain experience on the data science lifecycle, and explore various data science career paths providing a complete guide on how to start a career in data science.

Data science course duration

On average, a data science course spans from 6 months to 3 years, depending on the curriculum, projects, and student availability. 

For instance, the data science course from IIT Madras is at least 2 years long and can stretch up to 3 years.  

ExcelR, a reputable choice among data science learners, provides a 6-month data science course. It also has various branches in different locations in India. 

Who is eligible for Data Science courses?

If you want to enroll in any online training course for Data Science, there are no such criteria or eligibility. However, knowing the basics of computers and data science fundamentals will be helpful.

For academic courses in India: Students are eligible for Data Science courses after completing their 12th grade, with specific criteria depending on the course type:

• Diploma in Data Science: Open to any stream with 10+2 completion.
• BTech in Data Science: Requires 10+2 with Physics, Chemistry, and Mathematics, along with a minimum of 50% marks.
• B.Sc/ BCA  in Data Science: Eligible for students who have completed 10+2 with Mathematics, also need at least 50% marks.
• Postgraduate Courses: A bachelor’s degree in IT or related fields is necessary, with a minimum of 50% marks required.

But, with the vast number of options available in the market, choosing the right course can be difficult. Our list of data analytics courses in Pune will help you make a choice.

1. IIM SKILLS Data Analytics

GMB rating: 5/5

Placement assistance: Yes (guaranteed placement is entirely based on merit)

Certification available: Yes

Course duration: 6 months

Price: INR 49,990

Course type: Non-academic

Teaching mode: Online

This comprehensive course equips you with essential skills in statistics, SQL, and Python. Master Python programming, and data manipulation with Pandas, and implement machine learning using Scikit-learn. Learn Excel and Microsoft analytics, delve into visualization tools like Power BI and Tableau, and gain expertise in data interpretation and analytics techniques.

Modules covered/Syllabus

Data analytics using:

• Advanced Excel
• VBA
• SQL
• Power BI
• Python- 1 and 2
• Tableau
• R for Data Science 
• Alteryx 

Why enroll in this course?

Unlock a diverse skill set, spanning statistics, programming, and analytics. From mastering Python to utilizing powerful visualization tools, this course empowers you with the tools needed for effective data analysis and interpretation, making you a well-rounded data professional in high demand.

2. Ethans: Data Science Course

GMB Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 100 hours 

Price: (or add a range)

Course type: Industry Oriented Curriculum

Teaching mode: Online + Offline

This industry-centric course is suitable for analytics enthusiasts and career switchers. This course covers fundamentals from Statistics, SQL, and Python programming to advanced AI, Machine Learning, Business Analytics, and Text Analytics. Ideal for diverse professionals, it equips you to meet industry demands and transforms you into a career-ready Data Scientist.

Modules covered/Syllabus

The module contains but is not limited to:

• Various Python concepts.
• String, list, tuple, dict, set, frozenset, and Boolean data Types.
• Developing functions using Lambda statements.
• Generators, Decorators, and Closures.
• PDB debuggers and Pycharm Debuggers.
• Design Patterns Techniques with OOPS.
• RDBMS-SQLite3 database Handling.
• Numerical Python and Statistical Analysis.
• Dataframe and Series in Pandas.
• Different Files Reading Techniques.
• Introduction to SkLearn Library.
• Seaborn – Exploratory data analysis Library.
• Introduction to Statistics.

Why enroll in this course?

The course is best for career changers, and professionals seeking to excel in Data Science, as this training offers a holistic curriculum. From foundational concepts to advanced techniques, including AI and Machine Learning, this program ensures you’re well-prepared for the booming Data Science industry, guided by expert trainers for a successful transition.

Relevant: Best data analytics courses for Indore

3. 360DigiTMG: Data Analytics

GMB Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course Duration: 48 hrs classroom/online session + (80+) hours assignment and e-learning + (80+) hours live projects 

Price: ₹36,000 + Tax

Course type: Industry-centric Certification Course

Teaching mode: Online and Offline

The course helps to discover techniques for handling vast data sets through Data Analytics. Explore applications of data storage, processing, and analysis technologies. Learn to analyze structured and unstructured data, create visual narratives with Tableau or PowerBI, and grasp essential tools like SQL, NoSQL, Tableau, PowerBI, and Advanced Excel.

Solving real-world case studies enhances your ability to make data-driven decisions and build impactful visual reports.

Modules covered/Syllabus 

• Data handling
• Tableau 
• Python
• R
• PowerBI
• SQL
• NoSQL
• Advanced Excel

Why enroll in this course 

The course is best suited for professionals who want a career switch or looking for upskilling. The course equips professionals with the skills to manage, analyze, and visualize data effectively. Real-world case studies enhance problem-solving abilities, making you adept at transforming data into actionable insights for enhanced business outcomes.

4. Intensive 2.0: Data Analyst Course

GMB Rating: 4.5/5

Placement assistance: Yes

Certification available: Yes

Course duration: 5 months

Price: ₹90,000 (Pre-paid) / ₹55,000 + 12% of annual CTC (post-paid)

Course type:  Industry-centric Certification Course

Teaching mode: Online

This comprehensive data analytics course is great for students who completed their degree and want a course that can help them land an entry-level job as Jr. data analyst, business analyst, data transformation analyst, etc. It has both fundamentals and data analyst specializations with 10+ project-based learning. 

Modules covered/Syllabus 

• Python
• SQL
• Advance SQL
• Descriptive statistics
• Data Visualization
• Data Cleaning
• Data Transformation
• Data Modelling
• Dashboard Creation
• Tableau
• Numpy
• Pandas
• Power BI

Why enroll in this course 

No prior experience in coding is required. You learn through real-time project handling, which will also add to your resume also comes with a 24*7 state-of-the-art online lab to practice what you learned.

5. Edureka: Data Analytics Masters Program 

GMB Rating: 4.8/5

Placement assistance: No

Certification available: Yes

Course Duration: 150+ hours

Price: ₹69,999

Course type:  Industry-centric Certification Course

Teaching mode: Online

This data analytics course focuses on strengthening individuals by giving them knowledge of the latest tools and systems used by data analytics professionals. The course is meticulously curated based on job descriptions and the skills required to bag a high-paying job as a data analyst.

Modules covered

• Statistics
• Data analytics with R programming
• Tableau
• Microsoft Power BI
• AWS S3

Why enroll in this course 

The course specifically targets what one needs to learn to get a job in MNCs like Google, KPMG, Amazon, etc, in the role of data analyst.  Apart from the modules, you get to choose one free elective module with trending options like QlikView, Machine learning, SAS, Advanced Excel, Decision tree modeling, etc. 

6. Sevenmentor: Data Analytics 

GMB Rating: 5/5

Placement assistance: Yes

Certification available: Yes

Course Duration: 90 hours

Price: NA

Course type: Cohort-based non-academic course.

Teaching mode: Online + Offline

A beginner-friendly course in basic, easy-to-understand language so that the language barrier is not a hurdle in your learning path. The teaching is project-based, so you get to explore concepts through application.

Modules covered/Syllabus

• Various aspects of data analytics
• Hive
• R
• Scala
• SQL
• Data analytics ecosystem 
• Commercial distribution etc 

Why enroll in this course?

Students can learn in their one-to-one coaching sessions, which is often great for beginners who require more attention or experts who want to save time. Their data analytics course has a variety of certification courses ranging from beginners, and college students to advanced level boot camp.

7. Simplilearn: Data Analyst Course

GMB Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course Duration: 11 months

Price: ₹57,000

Course type: Industry-based course 

Teaching mode: Online

This course is a collaboration between IBM and Simplilearn, a comprehensive course with industry-relevant learnings. The course is apt for professionals who are working in IT, Naking, finance, and similar sectors to gain a competitive edge. 

Modules covered/Syllabus

• Business analytics with Excel
• SQL
• Programming basics and data analytics with Python
• R programming for Data Science 
• Data analytics with R
• Tableau
• Power BI

Why enroll in this course? 

As the course is made with the collaboration of IBM, you get access to the IBM cloud platform that features IBM Watson and other software. You also get USD 1200 worth of IBM cloud credits that you can use for hands-on exposure, and the Jobassist program is great for absolute freshers. 

8. Excelr: Data Analyst Certification Course

GMB Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course duration: 6 months

Price: ₹44,999 (virtual class) and ₹59,999 (Classroom training)

Course type: Industry-specific learning.

Teaching mode: Classroom training and live virtual class

The Course focuses more on fresh graduates who have little to no prior job experience and want to enter the field of data analytics. All the necessary aspects like advanced Excel, Tableau, MySQL, and there, along with interview preparation training. 

Modules covered/Syllabus

• Database concepts
• Faya visualization
• Advanced Excel
• MySQL
• Tableau
• Power BI
• Business Statistics
• Python R Programming
• SAS

Why enroll in this course 

The alumni base is extensive and comprises one of the biggest MNCs. And with the real-life project-based Bootcamps, you get to prepare your portfolio alongside learning. 

9. Datamites: Data Analytics Course 

GMB Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 6 months 

Price: ₹57,855 (live virtual class), ₹62,605 (Classroom training)

Course type: Industry-specific learning

Teaching mode: Online + Offline 

This no-code data analytics course comprises all the necessary aspects you need to learn to land a data analyst job, such as Excel, MySQL, Tableau, and Power BI. The Government of India, NASSCOM, IABAC, and similar other prestigious institutions authorize the course. 

Modules covered/Syllabus 

• Fundamentals of data analytics
• Fundamentals of Python
• Advanced data analytics 
• Predictive analytics with ML
• Version control with GIT
• SQL and MongoDB
• Big data fundamentals

Why enroll in this course 

The course is customizable based on your needs, and you can choose whether you want self-learning through live mentoring or prefer in-person classroom training. 

10. DataTrained: PG Data Analyst, ML & NN

GMB Rating: 4.5/5

Placement assistance: Yes

Certification available: Yes

Course duration: 12 months (with 6 months internship)

Price: INR 1,60,000

Course type: PG course

Teaching mode: Online + Offline

This course is suitable if you are trying to learn data analysis along with state-of-the-array technologies like AI and ML. The course is aligned to comply with SSC NASSCOM. You learn through 40+ live projects and case studies with one-on-one interactions with mentors. 

Modules covered/Syllabus

• Excel
• Python
• Tableau
• NLP
• SQL
• Prompt query resolution

Why enroll in this course?

With this course, you get a total of four certifications, along with a 100% job placement guarantee. Best for those who are planning to learn more about booming industries like AI and ML.

11. IntelliPaat: Data Analytics Course

GMB Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course Duration: 7 months

Price: ₹70,053

Course type: Industry-specific learning

Teaching mode: Online + Offline

The course is made in collaboration with IIT Madras, hence you learn directly from the college faculty. The course comprises advanced learnings like ML, cluster analysis, data processing, cleansing, transformation, data visualization, etc.

Modules covered/Syllabus 

•  Data Transformation using MS Excel and Python
• Data wrangling with SQL
• Presto
• Business Problem Solving, Insights, and Storytelling
• KNIME
• Statistics and Machine Learning using R Programming
• Time-series forecasting, etc. 

Why enroll in this course?

You get campus immersion at IIT Madras Research Park and get hands-on training from the faculty. And you get exclusive access to the Intellipaat job portal apart from direct placement assistance. 

12. 3RITechnologies: Data Analytics Course

GMB rating: 4.4/5

Placement assistance: Yes

Certification available: Yes 

Course duration: 5 months 

Price: NA

Course type: Job-Oriented training 

Teaching mode: Online live training 

This course from 3RITechnologies covers all the essential skills you require to become a data analyst in 2024. Besides learning fundamental concepts of statistics and data Analytics, MS Excel, and RDBMS, students will also learn the use of analytics in machine learning, artificial intelligence, and deep learning.

Students will get an opportunity to work on 4 live projects under the mentorship of experienced trainers who conduct training with real-time scenarios. Upon successful course completion, you not only earn an industrially recognized certificate but also get expert support to land good jobs.

Modules covered/Syllabus

• Fundamentals of Statistics & Data Analytics
• MS Excel
• RDBMS Basics of SQL
• Python for Data Analytics
• Machine Learning
• Artificial Intelligence & Deep Learning
• GIT: Complete Overview
• Machine Learning in Cloud
• Data Visualisation with Tableau/PowerBI

Why enroll in this course?

This course is suitable for aspiring data analysts with a graduation or post-graduation degree or are professionals working in IT and non-IT sectors. There is no prerequisite for enrolling in this program, and you can learn data analysis through real-life industry projects sponsored by top companies across the industry.

Additionally, they arrange one-to-one career counseling sessions and mock interviews with hiring managers for your professional development.

13. TECHNOGEEKS: Data Analytics Course 

GMB rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 175 hours

Price: NA

Course type: Industry-based, job-oriented training 

Teaching mode: Instructor-led Live Interactive Sessions and classroom session 

This data analytics course is designed by IT professionals to ensure that students can learn the latest trends in the industry. Besides data analytics knowledge, you will have an in-depth understanding of Python programming language. The experts train you with 23+ data science tools, including Jupyter, Colab, Matplotlib, NumPy, Flask, Rest API, Pandas, etc.

After course completion, you will get a shareable certification and one year of access to the recorded teaching sessions.

Modules covered/Syllabus:

• Introduction to Python Programming
• Setting Up And Installations
• Python Object And Data Structures Operations
• Python Statements
• UDF Functions And Methods
• File And Exception Handling
• Python Modules And Packages
• Object Oriented Programming
• Advanced Python Modules
• Package Installation And Parallel Processing
• SQL
• Rest API With Flask And Python
• Rest API Integration With Databases For Web App Development
• Data Wrangling With Python And EDA (Exploratory Data Analysis)
• Data Analysis using Advance Excel
• Data Analysis With Python
• Data Analysis Using Numpy
• Data Analysis In Python With Pandas And Advanced Analysis
• Data Visualization With Python
• Data Visualization With PowerBI

Why enroll in this course?

This course aligns more with practical learning sessions, and students can work on two major real-time projects and use GitHub. Besides training you on data analysis, the experts assist students with mock interviews, resume building, and sharing of real-world data analysis and visualization experiences.

14. Learnbay: Data Analytics Course 

GMB rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 180 hours

Price: ₹85,000 + GST

Course type: Industry-Oriented learning

Teaching mode: Live Interactive learning sessions 

This data analytics course is for early professionals who want to develop their career paths but have no coding skills. You will start learning data analytic tools along with knowing basic Python and R programming, statistics, and basic machine learning concepts.

Upon successful completion of the course, you get globally recognized certification from IBM and land a high-paying job.

Modules covered/Syllabus:

• Python programming (Basic + Advanced)
• Statistics & Basic Machine Learning
• Data Analytics Tools (SQL, MongoDB, Tableau, PowerBI, Big Data & Spark Analytics, Time Series)
• Excel
• AI Generative Tools and Future Trends
• Python Bootcamp for AI
• Build Your Interview Assistant
• Large Language Models (LLM)
• Visual AI for eCommerce
• Intelligent News Aggregator
• Azure OpenAI Integration 

Why enroll in this course?

With this course, you can work on 5 real-time projects from multiple industries, like banking, healthcare, finance, etc., in a group that improves your collaboration skills and project management skills. You get 11 doubt-clearing sessions during the course period. If students aren’t satisfied with their mentors, they can raise an issue and change their mentors. 

Relevant data analytics resources:

• Key differences between data analytics and business analytics
• Find the top data science courses in the US

Find the right data analytics courses in different regions:

• Indore data analytics courses
• Mumbai data analytics training programs
• Hyderabad data analytics courses

What are the Data Analytics course fees in Pune?

The data analytics course fees in Pune range between ₹5000 – ₹1,60,000 and more. The course fees are determined after considering multiple factors like the course syllabus, course duration, reputation of the institution, experience of the trainer, practical sessions with live projects, institute location, etc.

However, you can find numerous free data analytics courses available on YouTube. 

What is the salary of Data Analysts in Pune?

The average salary of data analysts in Pune is around ₹6.5 LPA. An early-stage data analyst may start working at a lower salary of ₹1.8 LPA in Pune, but with about 6 years of experience, they can earn around ₹8.2 LPA, rising to nearly ₹10 LPA or more.

The salary of a data analyst largely depends on their position in the company, the size of the company, work complexity, skill set, and experience. 

Who is eligible for data analytics courses in Pune?

Anyone with a knack for Data analytics is eligible for data analytics courses in Pune. However, having a basic college degree in any subject is essential, along with having strong analytical and problem-solving skills.

Here’s a list of people who can enroll in data analytics courses.

• A graduate or a postgraduate student (both IT/non-IT)
• Working professionals willing to upskill or switch jobs (IT/non-IT)
• Business owners making data-driven decision
• Marketers and sales professionals for improved marketing campaigns
• BI professionals, project managers, software developers, information architects, etc.

How can I become a data analyst in Pune?

Whether you are starting your professional career or looking for a job change in the data analytics domain, you have proper knowledge about the subject, acquire skills to stand out from the competition, gain certifications, and try landing your first job.

Here’s a step-by-step guide for data analyst enthusiasts to secure a good job.

1. Get qualified as a data analyst 

You can enroll in different Data Analytics courses that will provide you with course completion certificates. These showcase your qualifications and knowledge about data analytics to potential recruiters. 

If you are enrolling in majors like data science, computer science, applied mathematics or statistics, and Management Information Systems, these courses cover basic Data Analytics skills along with other subjects.

However, if you haven’t graduated from these majors, you can enroll in a Data Analytics course suitable for non-IT students that prepares you as a data analyst from scratch. These short-term or long-term Data Analytics courses offer industry-accredited certificates that help you land a good job.

2. Learn the basics of Data Analytics 

The first thing you need is an in-depth knowledge of data analytics. For beginners, you can enroll in a course that covers all necessary subjects and the use of data analytics tools. Some of the basic things you need to know are data manipulation and cleaning, data visualization, statistics and probability, SQL, big data technologies, Excel, any programming language (e.g., Java, R, and Python), Machine Learning basics, etc.

3. Work on multiple projects

The best way to learn data analysis is to work on live or real-time projects. Top Data Analytics courses offer you the opportunity to work on live projects under the mentorship of industry experts. This will help you get hands-on practice on different concepts of Data Analytics, understand real-world challenges in implementing such projects, and develop solutions.

You can get free data sets for your data analysis projects from DataLab, Kaggle, UCI Machine Learning Repository, FiveThirtyEight, etc. 

4. Develop a professional resume

As a fresher, when you are applying for a data analyst job, you don’t have work experience to showcase. However, recruiters will hire you based on the skills and expertise that they see in the projects you have done. Therefore, building a professional resume that showcases your projects and certifications is important. 

You can create a GitHub account and add all these projects to that account, then share its link to your resume. Share this resume to top job boards like Indeed, Glassdoor, etc., and social networking platforms like LinkedIn for direct contact with potential recruiters.

5. Gain global certifications

Earning global certifications can help you stand out of the competition to employers. They demonstrate your specific skills that can help companies solve existing issues with data analysis. Listed below are a few certifications that you can earn in 2024.

• AWS Certified Data Analytics
• Google Data Analytics Professional Certificate
• IBM Data Analyst Professional Certificate
• Microsoft Certified: Power BI Data Analyst Associate
• Cloudera Certified Associate (CCA) Data Analyst 
• CompTIA Data Analytics Plus Certification 
• Certified Analytics Professional (CAP)

6. Land an entry-level Data Analytics job 

You can start applying for entry-level Data Analytics jobs that don’t require much work experience, but skills and expertise are sufficient. These are trainee positions or junior data analysts who work in a team under the supervision of senior data analysts.

While searching for entry-level data analytics jobs, we found nearly 2,000+ jobs in India on LinkedIn.

Which Data Analytics Course To Follow In 2024 In Pune? 

Based on the data, IIM SKILLS, Ethans, 360DigiTMG, Intensive, and Edureka are our top five picks. Now, based on your requirements and budget, you can pick any of those.

While the field offers promising career prospects with a projected 27.9% growth by 2026 according to the U.S. Bureau of Labor Statistics, success demands mastery of both technical and soft skills.

This comprehensive guide outlines the essential steps to launch your data science career in 2025, from educational requirements and skill development to practical experience through internships and certifications.

• What is Data Science?
• What does a data science engineer do?
• How to start your data science career
• Important data science skills to master
• Roles and Responsibilities of a data science engineer
• Is it hard to get a job as a Data Scientist?
• Is a career in data science worth it?
• Final Words

What is Data Science?

Data science is the field of study that combines subject-matter knowledge, mathematics, statistics, artificial intelligence, and computer engineering to draw out useful insights from data.

Data science’s primary purpose is to collect, process, analyse, and filter information from raw data.

Data science uses the most advanced hardware, programming languages, and algorithms to resolve data-related issues.

The future of artificial intelligence lies in it.

Simply expressed, data science is all about:

• Presenting the right questions and analyzing the raw data
• Using various advanced and effective algorithms to model the data
• Visualizing the data to gain a deeper understanding
• Understanding the data to find the final result and make better decisions

What Does a Data Science Engineer Do?

A data engineer is responsible for creating systems for gathering, validating, and preparing high-quality data. Data engineers collect and prepare the data, while data scientists use the data to support better business decisions.

The data engineer/ strategist’s job is to find and integrate new datasets that can be used to expand the functionality of the business and collaborate with the technical team to develop data products.

Relevant read: How long does it take to learn data science?

How To Start Your Data Science Career?

There are a few questions you should ask yourself before planning to pursue a career as a data scientist:

• Do you love statistics, numbers, and graphs? Data science is entirely based on Maths and statistics. If you don’t like math, statistics, and numbers this is a red flag for you. If you don’t like working with numbers, you will find your job frustrating later in your career.
• Before advancing to a justified data scientist position, are you willing to learn and work at the entry-level?
• Are you able to program easily? Data scientists should be comfortable using a variety of programming languages, including R and Python.

You can move forward and begin learning the data science abilities once you have a positive answer to the questions above.

Let’s take a look at the steps to Becoming a Data Scientist

Step 1. Get an undergraduate degree in data science

To become a data scientist, you must first get an undergraduate degree in data science or a closely related field.

Most employers will want to see a bachelor’s degree to hire you as a data scientist. Getting a bachelor’s degree in a field like data science, statistics, or computer science is an excellent way to get started in this profession.

 A senior professional with a bachelor’s or master’s degree in IT/ computer engineering can pursue a career in data science by upgrading and retraining through online data science courses in the US.

Otherwise, if you’re looking for a data science boot camp, post-graduation course or master’s in data science, GreatLearning’s online data science courses are a good place to start.

Here are some of the latest data science courses that you can enroll:

• MIT data science
• PG data science course
• Data science course in IIT

Find the latest data science job statistics.

Step 2. Develop your skill set

Even though a Bachelor’s degree may give you a theoretical understanding of the topic, it is important to brush up on your programming, technical, and non-technical skills.

Below are some of the most necessary skills you require for this job.

•  Programming languages like  Python, R, SQL, SAS, Java, Julia, JavaScript, Swift, Go, MATLAB, SAS
• Technical skills include machine learning, deep learning, processing large data sets, data visualization, data wrangling, statistical analysis and computing, mathematics, programming, statistics, and big data.
• Non-technical skills like strong business acumen, strong communication skills, and great intuition regarding data that you are working on.

Check out our list of top data science books that will upgrade your skill sets.

Step 3. Get Certifications in Data Science

Getting Data Science Online Courses & Certifications is a great way to showcase your skills.  Instead of buying random data science courses on the internet, try to get free certification from trustworthy sources like Simplilearn, Naukri, and LinkedIn.

Here are some data science courses and certification programs to help you on your way:

• Tableau Certification Training Course
• Expert instructor-led data science online course (6 months)
• Power BI Certification Course
• Data Science Online Courses
• Certifications in Data Analytics
• Data science with Python
• Data engineering and smart analytics

These two are the most widely used tools among data scientist professionals and would be an excellent addition to begin your career journey.

Step 4. Find Internships and Entry-Level Jobs

The best way to enter the data science field is through an internship. Find a position that can help you improve your skills and help you to grow in your career.

After your internship, you can either stay with the same firm (if they are hiring) or hunt for entry-level opportunities for data scientists, data analysts, and data engineers.

You can earn experience and work your way up in your career as your knowledge and skills expand.

At WebPipl, we use AI and NLP technology to help identify top tech candidates, but we also rely heavily on our recruiters to ensure that we’re selecting candidates who are the right fit for our company culture.

To crack interviews with tech recruiters, candidates should focus not only on showcasing their technical skills, but also on demonstrating their ability to collaborate with others, solve problems creatively, and communicate their ideas effectively.

– Contributed by Raju Thammala (founder of WebPipl)

Relevant read: Learn how to get a data science internship (full process)

Step 5. Go for Higher education

While a bachelor’s degree may be sufficient to get you started in the ideal job and gain the necessary real-world work experience, a master’s degree in data science would help you to enhance your knowledge and empower you to grow in your field.

This work experience can make you more appealing to an employer for a high-level Position like a Data scientist. Here are some master’s degree options available:

• Master of Computer Science in Data Science
• Master of Data and Network Analysis
• Master of Applied Data Science
• Master of Science in Data Science

Important Data Science Skills To Master

There are two different types of skills required to master data science:

1. Technical Skills

Statistical analysis and computing, Machine Learning, Deep Learning, Processing large data sets, Data Visualization, Data Wrangling, Programming, and ig Data are some important technical skills that are required in master data science

2. Non-technical skills

Some of the most important Non-technical skills include Strong Business Acumen, Strong Communication Skills, and Great Data Intuition. You need to have the skill to make the right judgments and make quick decisions in this job.

Roles and Responsibilities of a data science engineer

1. Collecting data from different sources

Identifies and pulls relevant data from diverse sources via SQL, APIs, and web scraping into cloud data warehouses.

• Identify relevant data sources such as databases, APIs, websites, sensors
• Build data collection pipelines to gather, extract and move data
• Clean unstructured data to prepare it for analysis

2. Exploratory data analysis

Summarizes visualizes and statistically explores the raw data to uncover initial patterns, anomalies and hypotheses.

• Create data summaries, visualizations to understand data patterns
• Identify relationships between variables, data discrepancies
• Perform statistical analysis to derive initial insights from the data

3. Preparing data for modelling

Cleans data, imputes missing values, engineers helpful features and selects meaningful variables so models can best leverage the data.

• Handle missing data, outliers
• Engineer new features by transforming variables
• Perform feature selection to remove irrelevant variables
• Encode categorical variables for machine learning

4. Building machine learning models

• Try out different modelling techniques like classification, regression
• Fine-tune model hyperparameters to improve performance
• Evaluate models using relevant accuracy metrics
• Perform cross-validation to measure robustness

5. Deploying and maintaining models

Containerizes models via Docker, pushes them to prod via DevOps pipelines then monitors their performance to ensure continued reliability and retrains as appropriate.

• Put models into production via tools like SQL, Python
• Monitor model performance to detect concept drift
• Retrain models on new data to keep them relevant

6. Software engineering

Leverages languages like Python and R to write clean, reusable code under version control to track updates and enable seamless collaboration with others.

• Write reusable modular code for data processing tasks
• Version control code changes using Git and collaborate using GitHub
• Containerize data science workflows with Docker for reproducibility

Here’s a data science career tip from a data scientist:

Focus on Core Fundamentals

Start by gaining a solid understanding of statistics, mathematics, and programming, and then apply these skills by working on projects that interest you to gain practical experience and build a portfolio that showcases your abilities.

Continuously learn and stay up-to-date with the latest advancements in the field. Network with other professionals and attend industry events to expand your knowledge and build connections in the field. 

As a data scientist, it’s crucial to have strong documentation skills in order to effectively communicate technical details, insights, and results to stakeholders. Documentation not only helps to ensure the reproducibility and transparency of your analysis but also facilitates collaboration and knowledge transfer within teams and projects.

I highly recommend investing time and effort into learning how to create effective data science documentation.

Contributed by Edward Pinela III, Senior information technology project analyst and CEO at Lightray Solutions

Is it hard to get a job as a Data Scientist?

A Data Science job is not as easy as it looks. It is not a field where you can get a job after taking a 15-day course. Data Science requires discipline, and determination while learning.

Data science is the field of people who are interested in numbers, Stats, and engineering.

Most people choose this career because of its perks and high demand, despite the fact that this field does not interest them in any way.

“Businesses seek out talented individuals for Data scientist positions. Getting a data science course certificate does not make you a data scientist.

You need expertise, Knowledge, and years of experience to be a data scientist.”

Ronald Van Loon (Big data and Analytics Course Advisor at Simplilearn)

In an interview with Simplilearn, he talks about developments that will drive the need for more data scientists in the future and the current state of demand for data scientists.

Although, you can apply for entry-level data science jobs like data engineer and data analyst with an undergraduate degree and data science courses.

Not sure which job profile to choose in data science?

Check out our guide on different job types in data science where we have shared important job profiles to consider before choosing your career.

Is a Career In Data Science Worth It?

Yes, a job in data science offers excellent opportunities for the future. Data science professions are among the most rapidly increasing and in-demand in technology.

According to the US Bureau of Labor Statistics, demand for data science skills will rise by 27.9% by 2026.

According to a McKinsey report, this will result in a shortage of between 140,000 and 190,000 analysts in the United States alone.

When I checked on Google Trends, I found that the search demand for the term ‘data science’ has increased by 95% worldwide in the last 5 years.

Glassdoor has referred to a Data Scientist job as the “greatest job in America” and LinkedIn has labelled this job title as “the most promising career” because of its high demand, attractive salary, and all other benefits that come with it.

The US Bureau of Labor Statistics predicts a whopping 36% growth in data scientist jobs by 2031, significantly outpacing the average job market. This translates to a wealth of opportunities for qualified data scientists.

The beauty lies in its flexibility. Even if your academic journey is on a different track, a data science minor can be the perfect bridge. Many universities now offer this interdisciplinary minor, allowing you to seamlessly integrate data science skills into your existing major.

Here’s why a data science minor is a strategic move:

• High Demand, High Value: The data science minor equips you with exactly what employers seek – practical data analysis skills, machine learning proficiency, and statistical modeling expertise. With this in-demand skillset, you’ll stand out in the job market.
• Diverse Career Paths: As data becomes the cornerstone of decision-making across industries, a background in data science opens doors to a wide range of exciting career paths.

– Sai Sathish, Marketing and tech product head at Consainsights, a market research and consulting firm.

Further resources:

• Understand what is data curation in data science.
• Looking for companies to apply as a data scientist? Look at the top data science companies In Bangalore.

Final Words

The demand for Data scientist jobs has increased with their salaries and Data Scientists can often expect to earn six figures. Demand in this field also allows you to relocate much more easily, both domestically and abroad.

Before Pursuing this career, make sure this field of data and numbers interests you or else it will be difficult for you to survive in this field in the future. This guide provides guidance that can get you started with your data science career and help you to avoid some costly mistakes.

Article by

Samruddhi Chaporkar

Samruddhi is a Technical Content Writer of science and technology with an academic qualification in Bachelors in Computer Applications (BCA). Her love for writing and knowledge of computer science helps her write about trends in the technology industry that help people understand the ins and outs of the world of technology.

LinkedIn | Twitter | Author page

The goal?

To understand the current state of the data science job market. This includes studying:

• Average data science salary
• Role of experience in payscale
• Breakdown of average salary by regions
• Top data science skills demanded by recruiters 
• Minimum qualification to become a data scientist
• Industries with the most number of data science jobs, etc.

Key highlights of the study

• Full-time jobs make up the vast majority (91.8%) of available data science jobs.
• Part-time jobs (2.3%), tenure track (1.0%), and temporary positions (0.6%) are relatively uncommon for data science roles.
• The Information Technology sector has the highest number of available data science jobs (34.5%).
• Other top industries include Management & Consulting (10.9%), Finance (10.6%), and Education (10.7%).
• Manufacturing (1.3%) and Retail & Wholesale (1.2%) have the least number of data science job openings.
• Python, Machine Learning, Data Science, and SQL are the most sought-after skills for data science jobs.
• Most data science jobs require at least a Bachelor’s degree (49%).
• A Master’s degree (38%) can increase the chances of getting a higher-paying job.
• Doctoral degrees (8%) are typically required for research and development roles.
• Data science salaries increase significantly with years of experience, from an average of $78,800 for 0-4 years to $130,000 for 20-24 years of experience.
• Apple ($174,214), Capital One ($166,053), and Meta ($163,518) are among the highest-paying companies for data scientists.
• There is a gender disparity in the data science field, with 67.8% of data scientists being male and only 31.2% being female.
• The United States ($132K – $190K), Australia ($114,788), and Canada ($103,522) offer the highest average annual salaries for data scientists.
• Countries like India ($13.3K) and Sweden ($48.13K – $63.39K) have relatively lower average salaries for data scientists.

1. What is the distribution of available jobs across different job types?

The chart above shows the distribution of available data science jobs across different job types based on a sample size of 12,852 jobs. According to the report, full-time jobs make up the vast majority (91.8%) of the total, and the next highest percentage is contractual jobs. 

Part-time jobs are only 2.3% of the total. And tenure track positions and temporary positions are even less, with 1.0% and 0.6%, respectively. 

It can be because most data scientists are involved in long-term continuous projects, thus not suitable for part-timers or tenure-based people. 

Plus it takes time for a data sciences person to get accustomed to all the ins and outs of the business to give valuable feedback. Changing them frequently will waste a lot of time in onboarding, defeating the purpose of being efficient.  Besides temporary employees, there can be an issue of data breach and loss of confidential data. 

Therefore, your chances of getting a data science job in India will be highest if you look out for full-time positions. 

2. Which industry has the highest number of available data science jobs?

The data suggests that based on a sample size of 12,117 data science jobs, the majority are recruited in the IT sector. Management & Consulting (1,325 jobs) and Finance (1,287 jobs) are the other two sectors with a significant number of data science job openings, at 10.9% and 10.6% respectively. 

It can be because all of the above-mentioned industries require help with aspects like fraud detection, process automation, customer segmentation and so on to take more data-driven actions. 

However, you also get scope in sectors like Education (10.7%), Aerospace & Defence (7.4%), Healthcare (5.7%), and Pharmaceutical & Biotechnology (7.1%). 

In the education sector, you are most likely to secure a teaching job, as more and more school graduates are eager to learn data science. 

While in aerospace and defence, you can expect to perform predictions, anomaly detection and root cause analysis of aircraft. 

In healthcare, data scientists use data to diagnose illnesses, develop personalized treatments and detect patterns to indicate the emergence of infections and diseases. 

But the least number of data science job openings are in sectors like  Energy, Mining, & Utilities (4.7%), Insurance (2.7%), Retail & Wholesale (1.2%), and Manufacturing (1.3%). 

So, statistically speaking, you are more likely to get a data science job in an IT firm or management and consulting corporation. 

3. Which region offers the highest average salary in the US?

Where you get placed in the US also influences how much you get paid. According to our research, Rhode Island in the US pays the highest salaries for data scientists whereas Delaware pays the least. 

However, Rhode Island also has a higher (almost 13% higher than the national average) cost of living than most states in the US. California, New Jersey, and Washington also fall under the same category. 

So, if you want to spend less, you can look for jobs in regions like Arkansas that have a lower (around 14% less than the national average) cost of living. Or Georgia, where you can save a lot on basic necessities like housing, utilities, food, and healthcare. 

4. What are the top data science skills based on job descriptions?

1. Python 
2. Machine Learning 
3. Data Science 
4. SQL 
5. Deep Learning 
6. Data Analysis 
7. Artificial Intelligence 
8. Data Mining 
9. Analytics and Analytical 
10. Computer science 
11. R 
12. NLP 
13. Open Source

(n = 10246)

After analyzing almost 10,246, we found out that the top skill required for data science jobs is knowing the programming language Python. Python is not only used in the US but is also the most weirdly used programming language in the world for data science. 

The list above is in the order of most important to least important. So, once you learn Python, your next target should be Machine Learning, as it is a key component of data science, and data scientists use it to create models and algorithms that can help companies solve problems.

Although AI has been the talk of the town for quite some time now, it is not a big priority for data science jobs. You can keep it for later, along with skills like Natural Language Processing (NLP) and Open Source. 

5. What qualification is required for a data science job in 2024?

In most cases, you will need a bachelor’s degree in a relevant subject to get an entry-level data science job. However, if you can wait two more years and get a Master’s degree, your scope of getting a comparatively high-paying job increases.

Not many companies will ask you for a Doctoral Degree unless it is for a top-level data science job. However, if you want to be part of a research and development team, you will be required to have a PhD in Data science. 

There are not many employers who are candidates with high school diplomas or GEDs. So you at least need to complete your Bachelor’s degree to get a decent-paying job in Data Science. 

6. How does work experience level affect data science job salaries?

The difference in pay based on your years of experience is quite standard. 

As a beginner with 0-4 years of experience, you can expect to get paid $78,800 per annum. However, after five years, your pay might reach $96,800. It is a 22.84% increase in five years, which is around a 4.6% salary increment every year. 

From the table above, you can see that there is not much difference in the annual income of a person with 16-20 years of experience compared to a person with almost 4 years of experience.  

7. What are the highest-paying companies in the world?

The salary you can earn through data science significantly depends on the company you get to work in.  In the list above, we have presented all the top companies and their average annual salary for data scientist roles. 

According to our research, we were surprised to find that Apple pays the highest to data scientists. Whereas companies like Google, which presumably have a lot more association with big data, pay slightly less than that. 

Thus, it would be unfair to think that only IT companies pay the highest to data scientists. You should also look around at other Fortune 500 companies in different sectors like electronics and social technology companies. 

8. What is the gender breakdown of data scientists?

n = 2907

Unfortunately, the gender disparity is quite striking in data science careers. Based on 2097 responses, we discovered that almost two-thirds of the total number were males, while only one-third were female. 

There could be a lot of reasons behind that, including gender stereotyping, lack of role models, and poor career development due to working in a male-dominated workplace. 

However, the statistics should motivate females even more to pursue data science as a career and address this gender gap. 

9. What is the average base salary of data scientists around the world?

Due to purchasing power parity (PPP), salaries fluctuate drastically in different countries. This is why you will find most of the first-world countries paying almost ten times more to the data scientists than what they get paid in India. 

But keep in mind that their cost of living is significantly high, too. 

So, where in India, you can live a comfortable life in a metro city with a salary of $13.3K/ annum, you might struggle with even $132K if you live in California (the US). 

For example, the average living cost in Indian metro cities is around ₹50,000 ($600)/ month for a single person. Also, here we are talking about an affluent lifestyle. 

But the same person would need to spend an average of $3,555/ month.  And it will even go higher for prime locations like New York, California, Florida etc. 

So, it is not always a great idea to move out to another country just because their pay seems tenfold better than what you are getting;  always consider the expenses, too. 

How we collected data

To get insights and statistics, we relied on publicly available data from various job portals such as LinkedIn Jobs, Payscale, Glassdoor, Talent, Indeed, etc. 

We then gathered and organized these into the report format to make a broader picture of the data science job market.

However, one limitation of this report is that over time the data may change depending on the job portals. This is why we will redo our research every year to make the report accurate and fresh.

Sources and references

• https://www.glassdoor.co.in/
• https://www.glassdoor.co.in
• https://www.talent.com/
• https://www.ambitionbox.com/
• https://www.indeed.com/
• https://www.indeed.com/
• https://www.indeed.com/
• https://www.payscale.com/

Summary

In summary, I can say that this is the best time for you to get into data science. In the next five to ten years, the demand for data scientists is going to go up. And with the right set of skills and the right choices, you can make millions. 

If you are already a graduate and want to start looking for jobs, remember the key highlights I shared at the beginning. Explore non-IT fields; don’t move out if it’s not necessary, and keep upskilling as data science is constantly. 

This is why I have created this guide with 4 key career paths for becoming a data engineer in 2024 and beyond.

Also, I have listed all related questions related to job outlook, salary scope, job demand and more so you can prepare your learning roadmap.

Is data engineering a good career path in 2024?

Yes, data engineering is a good career choice in 2024 because the demand for data engineers is on the rise, and it offers lucrative career options.

1. Industry demand: There has been a massive interest growth in the data engineering field for the past 5 years and will keep rising in the future. 

2. Job availability: LinkedIn lists nearly 2000+ data engineer job vacancies across India. You can search different job boards, including Glassdoor, Indeed, and more, to find active job vacancies.

3. Career options: Data engineering is one of the fastest-growing occupations globally. You get numerous career options, including data analyst, data quality engineer, data moderator, database engineer, data scientist and data architect.

4. Salary ranges: As per Ambition Box, the average annual salary for a data engineer is ₹10.8 LPA in India. 

What is data engineering?

Data engineering refers to designing and building systems that can collect and analyse raw data from different sources. This data is made usable for data scientists, analysts and executives to generate predictive models and show short-term and long-term trends. 

The data engineering process comprises four key phases, including data gathering, data processing, data storing, and making data accessible to users.

What Do Data Engineers Do?

Data engineers can assist in designing, constructing, and maintaining systems that gather, analyse, manage, and organise raw data and transfer them into usable, high-quality data. The primary goal of data engineers is to make data accessible for organisations to use for evaluation and optimisation of their performance. 

Listed below are some of their day-to-day tasks:

• Analysing and organising raw data
• Building improved data systems and pipelines
• Evaluating business requirements and objectives
• Understanding and interpreting short-term and long-term trends and patterns
• Performing complex data analysis and reporting results
• Gathering raw data from multiple sources and converting them in usable, high-quality data
• Finding ways to improve data quality and reliability
• Identifying different opportunities for data acquisition 

Data Engineering Career Paths in 2024

1. Data engineer specialist

Data engineer specialists are experts in data engineering and are looking to specialise in a specific domain of data that is essential for any organisation, such as customer data or product data. 

They also need to specialise in a certain capability of the data platform, like business intelligence, reliability engineering, or feature engineering. 

Years of experience required: 5+ years

Role type: senior level

Job responsibilities: 

• Project management, designing and building data models and optimal data pipeline architecture
• Process improvement, developing and maintaining data collection and processing systems, extracting data from multiple sources including client marketing databases, second and third-party data using Hadoop, SQL, spark, etc.
• Implementing data storage solutions across databases and data lakes, supporting specialists in new analytical proof of concepts and tool exploration projects
• Ensuring data consistency and accuracy using data validation and cleansing technique
• Collaborate with cross-functional teams to identify and address issues related to data, and with internal/external shareholders to manage data logistics 

Key skills required: 

• Relevant bachelor’s degree in computer science, informatics, statistics, information systems, and other relevant fields
• Proficiency in programming languages including Python, Java or Scala
• Experience with big data Technology, including Spark, Hadoop, and Kafka
• Knowledge in database management systems, including relational SQL and NoSQL databases, including Postgres and Cassandra
• Expert knowledge of metadata management and related tools
• Exposure to Azure data environment and familiarity with related tools
• Exhaustive experience in dimensional modelling for Data Marts
• Experience in working with data integration and ETL tools like Talend, Apache NiFi, and Informatica
• Experience with AWS cloud services including EC2, EMR, Redshift, RDS
• Experience with data pipeline and workflow management tools, including Airflow, Luigi, Azkaban, etc.
• Excellent communication and collaboration abilities
• Good problem-solving and analytical skills

Average annual salary: Average Base pay of ₹10 LPA – ₹18 LPA 

2. Data engineer manager

A data engineer manager is a professional who oversees the development and use of multiple data systems within an organisation. They are responsible for effective data management, formulation of data collection techniques, implementation of secure data handling and analysis procedures, and establishing data sharing rules.

Years of experience required: 2-4 years

Role type: Senior level

Job responsibilities: 

• Create and enforce policies and procedures for effective data management
• Managing and overseeing data professional employee teams
• Assign work, and monitor the completion of core duties, assignments and projects of the team
• Exercise control and authority over approving the work of all team members
• Coordinate and consult with internal senior Management on risks related to projects, concerns and financial issues
• Construct analytical systems including architectural directions, translate business issues into specific requirements to construct analytical solutions and identify data to support solutions
• Conduct feasibility study, capacity planning, and process redesigning or re-engineering of complex integration solution
• Establishing rules and procedures for data sharing
• Assisting in creating reports and data extraction

Key skills required: 

• Bachelor’s degree in computer science or relevant degree with 5 years of progressive post-baccalaureate experience in IT consulting industry
• Experience with data administration and management functions
• Experience with scripting languages (Python, Java, C++, Scala)
• Understanding of modern digital databases and information system technologies
• Minimum 2 years of experience in utilizing ETL tools
• Familiarity with Agile delivery methodologies in converting business and functional requirements into technical designs
• Working knowledge of message queuing, highly scalable ‘big data’ data stores, and stream processing 
• Developing large-scale ETL and DW solutions on cloud platforms or big data environment
• Strong project management, organisational and problem-solving skills 
• Experience with data pipeline and work from management tools (Azkaban, Luigi, Airflow)

Average annual salary: ₹21 LPA – ₹35 LPA (Base Pay)

3. Data Architect

Data architects must specialise in developing and optimising database models that help store and retrieve company data. They must support clients to take control of their data and gain valuable insights out of it by defining reference architecture. 

Years of experience required: 2+

Role type: mid to senior

Job responsibilities: 

• Defining and prioritizing client data requirements
• Developing database solutions for storing and retrieving company data
• Collaborate with other architects, infrastructure and software professionals to define metadata layers, technical solutions and optimal integration within existing customer IT landscape
• Installing and configuring database systems to ensure better functionality
• Analysing structural requirements for model software and applications
• Migrating data from legacy software to new systems
• Designing conceptual and logical data models
• Collaborating with project teams to ensure data collection meets the data standards
• Developing best practices and frameworks for functional and integration test around data pipelines
• Translating complex business and technical challenges into logical data models

Key skills required: 

• Bachelor’s degree in computer science, information technology or relevant fields
• Experience in building business intelligence designs and predictive Analytics
• Deep understanding of query and analytics tools
• Experience in using cloud-based software
• Proficiency in SQL, NoSQL, Python, ETL, and SQL server
• Understanding of machine learning and relational databases
• Strong collaboration and communication skills
• Fluency in using different programs and software
• Translate business requirements into data requests
• Experience in managing data sets and working with ETL and Data warehouse solutions.

Average annual salary: ₹17 LPA – ₹30 LPA (Base Pay)

4. Data Scientist

These professionals can manage big data using their mathematical, coding, and problem-solving skills and extract valuable insights. Data scientists can use this data to create better solutions that help organisations to meet their objectives and goals.

Years of experience required: 3+

Role type: mid to senior level 

Job responsibilities: 

• Accountable for delivery of advanced analytics solutions into Quantum’s core data assets
• Development and execution of a roadmap for the ongoing development of foundational data assets
• Project management including overseeing and delegating technical tasks among other data analysts
• Reviewing code and ensuring quality assurance of output produced by analysts
• Supporting the analytics lead with analytics architecture and solution designing

Key skills required: 

• Previous experience as a data analyst or data scientist
• Expertise in data mining
• Knowledge of machine learning and operations research
• In-hand practice with business intelligence tools and data frameworks
• Having strong mathematical problem-solving and analytical skills
• Excellent communication presentation skills
• Bachelor’s degree in computer science, engineering, or relevant field
• Experience with querying databases and statistical computer languages like Python, and SQL

Average annual salary: ₹7 LPA – ₹19 LPA (base pay)

Check out the tech career paths related to data engineering:

• Complete data science career paths
• Python career paths and job outlook
• Software engineering career paths 
• Solutions architect career roadmap
• Data science career path roadmap

Job Outlook for Data Engineering

Within a decade from 2018 to 2028, the data engineering job growth rate is expected to be 21%. There will be lakhs of vacancies in this domain over the next decade. 

The average salary for data engineers will also increase in the next five years. These professionals with a master’s degree in data engineering are expected to make an average yearly income of $117,324, and with a doctorate, it is around $127,334 annually. 

According to research, it is estimated that by 2030, the global market for Big Data analytics will experience a growth rate of 30.7%, which means reaching a value of $346.24 billion. 

Skills and prerequisites to become a data engineer

Data engineering is a broad and evolving field. There are numerous tools, frameworks and technologies used in data engineering, but mastering them all can be challenging. However, these few skills are essential to have while choosing the domain.

1. Programming skills

In data engineering, you might need to use technology like big data or machine learning. This requires you to have programming skills, including Python, C++, Scala, etc. You can start by learning Python, as it is a beginner-friendly language. Plus, Python can help you create data pipelines, integrations, automation, and analysis of data. 

2. SQL skills

SQL skills involve understanding how to solve complex datasets using SQL dialects. You must know about relational and nonrelational database systems that can help you in data storage and retrieval. 

1. Relational database: A relation database is an organised collection of data elements in a tabular form, and a predefined connection links them. 
2. Non-relational database: It is also known as a non-tabular database that can come in different forms depending on the type of data model.

3. Data modelling techniques

Understanding the concept of data modelling is essential in data engineering. It serves as the blueprint for building scalable databases and warehouses. With data modelling techniques, you can execute efficient data pipelines that form the backbone of data engineering projects. 

Popular data modelling techniques you must learn are:

1. ER (Entity-Relationship) Model
2. Hierarchical Model
3. Network Model
4. Relational Model
5. Object-oriented Database Model
6. Object-Relational Model
7. Unified Modelling Language Class Diagrams
8. Data Dictionary modelling technique

4. Expertise in ETL tools

Extract, Transform, and Load (ETL) tools help data engineers extract data from sources, convert them into analysable format and store that data in a  data warehouse. Data engineers must have expertise in ETL tools to help companies analyse huge volumes of data relevant to a specific business challenge. 

A few examples of popular ETL tools are:

1. Informatica PowerCenter
2. Apache Airflow
3. IBM Infosphere Datastage
4. Oracle Data Integrator
5. Microsoft SQL Server Integration Services 
6. Talend Open Studio

5. Additional skills and prerequisites to become a data engineer

There are a few more technical and soft skills you must have to become a data engineer. These include:

1. Knowledge of AWS cloud services
2. Understanding distributed systems like Hadoop
3. Acquiring machine learning skills
4. Knowledge of application programming interface (API)
5. Excellent presentation and communication skills
6. Strong collaboration and critical thinking skills

The Future of Data Engineering— Will AI replace data engineers?

No, AI isn’t going to replace data engineers anytime soon.

While data engineers find AI to be a threat to their career path, AI aims to improve their work quality. It can automate your repetitive tasks but cannot perform tasks that require complex critical thinking and problem-solving abilities. Engineers need to customise their solutions consistently to fit with the changing business needs that AI is incapable of. 

Even Though AI can analyse and process large volumes of data, they cannot innovate or think creatively. There are numerous other things that AI can’t do, like following ethics and regulations, communicating with the management and stakeholders, and adapting to new situations.

How Much Do Data Engineers Make?

Data engineering is one of the well-paid jobs in India and the US. They are being highly valued by companies across multiple domains. With hundreds of companies joining the Big Data bandwagon and generating valuable insights, demand for data-related jobs is increasing, as is the demand for data engineers. In the below tables, we have displayed the average data engineer salaries in the top 5 cities of India and the US.

The average data engineer salary in India by city (chart)

The average data engineer salary in the US by city (chart)

How Difficult is Data Engineering?

Lack of proper courses

Data engineering is an intense technical field that requires you to master using several tools and technologies constantly. It can be challenging for data engineers to keep pace with the rapid technical growth globally and learn the ins and outs of data engineering.

According to experts in this domain, there is a gap between the education provided during a course and the skills and experience required on the job. Most of the data engineering courses don’t include concepts that are needed in the real world over theoretical knowledge like data warehousing and data pipelines. 

Not many opportunities for Junior Data Engineers 

There are fewer opportunities available for junior data engineers in companies, which makes starting a career and acquiring skills difficult. Even though there are huge job vacancies for data engineers, you will find most of the companies are hiring engineers with 2-5 years of experience. 

Requirement for a wide variety of skills

Data engineering is a vast area that requires so many skill sets from programming, SQL, data pipelines, DevOps, Cloud, data warehousing, etc. This often becomes difficult for aspiring candidates to get them all under their belts. Mostly, candidates suffer when they need to navigate through so many software options available today. 

Data Engineering Career Opportunities in 2024

Data Engineering is a hot topic of the year and will stay in the news in the future. With the increased use of data, this domain has turned out to be a lucrative career option for students in Computer Science and engineering or other relevant fields. 

1. Better opportunities 

The Big Data Engineering services market is around $79.34 billion in 2024 and is forecasted to rise anywhere around $162.22 billion in 2029, rising at a CAGR of 15.38%. The largest players in the market are Cognizant, Infosys, Accenture, Amazon, Genpact, and Capgemini, who are currently hiring thousands of Data Engineers yearly. 

2. Multiple job options

One can start their career from being a junior data engineer immediately after completing a certified course. This opens multiple other career doors, including data analysts, managers of data engineering, data architects, data scientists, and chief data officer. Plus, data engineers are now in demand in multiple sectors, including marketing, healthcare, e-commerce and finance.

3. High demand, low supply

Data Engineer can be the best career choice for you in 2024 as the demand for these professionals keeps increasing. According to research, the expected data engineering job growth rate is 21% from 2018 to 2028. However, the supply of data engineers isn’t that high, giving you better opportunities. 

4. High salary 

The average annual salary of a junior data engineer in India is around ₹4.4 LPA,  which is nearly ₹30,923 – ₹ 32,224 per month. In the US, you can expect yearly pay of $1,25,173 as a junior data engineer and $1,77,033 as a senior data engineer. 

Top data engineering career opportunities for 2024 include:

• Data engineer/Big Data Engineer
• Junior Data Engineer
• Senior Data Engineer
• Cloud Data Engineer
• Data Architect
• Data Warehouse Engineer
• Business Intelligence Engineer

Data Engineering course certifications to start your career

To help you get started in a data engineering career, I have listed some of the best data engineering course certification programs:

1. IBM Data Engineering Professional Certificate

This online certificate program makes you ready for a junior data engineer within 5 months, covering essential topics including Python, relational databases, Linux commands and shell scripting, ETL and data pipelines, data warehousing, machine learning, and more.

2. Data Engineering Course by Intellipaat

This is a free online course available on YouTube that covers almost every part of data engineering within 8 hours. You get a basic understanding of data engineering, along with tutorials on Apache Spark, AWS Elastic Map Reduce, Hadoop, Azure Data Factory, and more. 

Once you finish the course, enrol for Google’s Cloud Data Engineer Professional Certificate with a registration fee of $200. 

3. Introduction to Designing Data Lakes on AWS by Coursera

If you want to start a career as a data engineer, you need to understand how to create data lakes. This certification course from Coursera will help you learn about data science, big data, analytics, scalable Data Lake, and Amazon web services within approximately 14 hours. Additionally, you will be enrolled in the AWS Cloud Solutions Architect Professional Certificate.

4. Data Warehouse Fundamentals for Beginners by Udemy

This certified course from Udemy helps you master the techniques to build a data warehouse for your organisation and apply key design principles of dimensional data modelling.

You can also learn how to combine various models in approaches to unify and load data within your data warehouse. It is one of the top courses for individuals willing to become data engineers, business analysts or database designers.

5. Edureka’s Data Engineering Course

This free data engineering course can clear your basics within 10 hours and train you on Hadoop, Apache Spark, Azure Data, etc. It can be a great starting point if you want to step into the data engineering domain. 

For certification, you can enrol for the Databricks Certified Data Engineer Professional exam for $200 and get a certificate on successful completion.

Is the data engineering career path a right fit for you?

Answer the following questions and calculate your scoring to self-assess whether data engineering is the right career path for you:

• Placement assistance
• Syllabus comprehensiveness
• Course fees
• Rating by students
• Course duration
• Training mode

To make your research easier, I have spent 10+ hours creating this list of data analytics courses in Hyderabad.

1. Data Analytics Course by NXTWave Intensive 2.0

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 5 Months

Price: ₹ 45,000 For PostPaid and ₹ 90,000 For PrePaid

Course type: Technical training program

Teaching mode: Online 

This data analyst course will help to land a software job as a data analyst. The comprehensive data analytics certification program makes it industry-ready. The course can be completed in 5 months as per schedule and there is no CGPA cut-off. 

No prior coding knowledge is required and you can learn from top-notch trainers. Up to 20000/- scholarships can be won while enrolling in this course. 1500+ companies have already hired NxtGen Learners. 

Topics covered in this course:

• Fundamentals
  ◦ Responsive Website Design
  ◦ Data Analyst Specialization
  ◦ Static Website Design
  ◦ Introduction to Databases
  ◦ Programming Foundations with Python
  ◦ Bootstrap
• Data Analyst Specialization
  ◦ Data Modelling & DAX
  ◦ Advanced-Data Visualization
  ◦ Data Cleaning and transformation using Excel / Power Query
  ◦ Data Analytics using Tableau
  ◦ Data Visualization
  ◦ Data Analysis using Python Libraries

Course highlights:

• Real-time project building 
• 24×7 Online State-of-the-art Labs to practice
• Resume preparation and soft skills training provided
• Get access to placement portals
• Learn skills like SQL, Python, data modelling, descriptive statistics and much more. 

Connect NXT WAVE

• WhatsApp: +91 9390111761
• Email: support@nxtwave.tech
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2. Data Analytics Course by Intellipaat

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 200 Hours or 7 Months

Price: ₹ 100,035

Course type: Undergraduate training program

Teaching mode: Online 

This data analytics course is provided in collaboration with Intellipat and IITM Pravartak ( Technology Innovation Hub of IIT Madras) in Hyderabad. You can become an expert in SQL statistics and R programming by learning from industry experts and IIT Madras faculty. 

50+ live sessions are spread over 7 months, and you can learn at your own pace. Get one-on-one interaction with industry mentors and, in the end, get a chance to build your LinkedIn profile and your resume. 

Topics covered in this course:

• Data wrangling with SQL
• Data Transformation using MS Excel and Python
• Visualisation using Power BI
• Statistics and Machine Learning using R Programming
• Predictive Modeling
• Advanced Machine Learning Techniques
• KNIME
• Data Science Capstone Project
• Presto
• Feature Engineering
• Time-Series Forecasting
• Data Science Execution Strategy

Course highlights:

• Any professional looking to upskill their career can enroll in this course
• Master your data wrangling, prediction algorithm, SQL and data visualization skills
• Learn about Power BI, Data mining, Time series from industry experts
• Get hands-on training in real-life projects and transform your career 
• Get a chance to work at Google, Microsoft, Genpact, Amazon and much more.

Connect Intellipaat

• Phone: +91-7022374614
• Email: Sales@Intellipaat.Com
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3. Data Analyst Master Certification Training Course by SimpliLearn

Rating: 4.5/5

Placement assistance: Yes

Certification available: Yes

Course duration: 6 Months

Price: ₹ 54000

Course type: PG/UG

Teaching mode: Online 

This course is in collaboration with IBM, making you an expert in Data analysis. Learn analytic tools and techniques and languages like Python and R from industry experts. This is a course designed and delivered for freshers and working professionals. 

Basic knowledge of mathematics is all you need to enroll in this course. The basic tools covered in this course are- NumPy, Excel, Pandas, SciPy, tableau, and many more. 

Topics covered in this course:

• Business Analytics with Excel
  ◦ Formatting Conditional Formatting and Important Functions
  ◦ Data Analysis Using Statistics
  ◦ Dashboarding
  ◦ Power BI
• Programming Basics and Data Analytics with Python
  ◦ Data visualization with Python
  ◦ Mathematical Computing using NumPy
  ◦ Data Manipulation with Pandas
  ◦ Statistical Computing
• Structured Query Language SQL
  ◦ Fundamental SQL Statements
  ◦ Alias
  ◦ Subqueries
  ◦ Pattern (String) Matching
  ◦ Mathematical Functions
  ◦ Aggregate Commands
  ◦ Group By Commands
• R Programming for Data Science
  ◦ Data Structures, Working with Data, Stings and  Dates in R
  ◦ R Programming Fundamentals
• Tableau Training
  ◦ Dashboard, Filters and Creating Charts in Tableau
  ◦ Core Tableau in Topics
  ◦ Applying Analytics to the worksheet
• Data Analytics with R
• Data Analyst Master’s Capstone

Course highlights:

• For comprehensive learning make use of capstone and 20+ industry-relevant Data Analytics projects 
• Eight times higher live interaction with industry experts from IBM
• At the end get a Simplilearn Master certificate 
• The program collaborated with online Bootcamp to help develop skills for real career growth

Connect SimpliLearn

• Phone: 1800-212-7688
• Email: support@simplilearn.com
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4. Data Analytics Certification Training Course  by EXCELR

Rating: 4.6/5

Placement assistance: Yes

Certification available: Yes

Course duration: 150+ Hours or 6 Months

Price:  ₹ 59,999

Course type: Technical training program

Teaching mode: Online and Offline

This data analytics certification training course in Hyderabad will help you to develop your career. This comes with intensive interview preparation and helps secure your dream job. The course, in collaboration with IBM, has a network of 2000+ hiring partners. 

Gain quality upskilling opportunities available for tech professionals and students. This course has been crafted as per market needs, and the tech domain is not dominated by coding.  

Topics covered in this course:

• MySQL 
• Tableau 
• Excel 
• Power BI
• ChatGPT
• Business Statistics 
• Fundamentals of R 
• Fundamentals of Python 
• SAS (Self Paced) 

Course highlights:

• Trainers at ExcelR carry 12+ years of industry experience
• Get knowledge about database concepts, functions, charts and sliders, and data visualization
• Learn about SAS’s self-paced and Large Language Models (LLM) and ChatGPT from this course
• Get intensive interview preparation from the first day of course enrollment

Connect EXCELR

• Phone: 096321 56744
• Email: enquiry@excelr.com
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5. Data Analytics Course Training by 360DigiTMG

Rating: 4.8

Placement assistance: Yes

Certification available: Yes

Course duration: 132+ Hours

Price:  ₹ 40,000

Course type: Post Graduate Diploma Certification Program

Teaching mode: Online and Offline

This data analyst course in Hyderabad is in collaboration with IBM. This will help to fast-track your career in handling huge data sets. Learn about the concepts of SQL, Tableau, PowerBI, NoSQL, and Advanced Excel from this course. 

360DigiTMG offers complimentary courses and resume-building sessions to make you industry-ready. Get lifetime LMS access and hands-on experience in live projects in this course. 

Topics covered in this course:

• Structured Query Language SQL
  ◦ DBMS vs. RDBMS
  ◦ Install PostgreSQL and MySQL
  ◦ SQL -Data Types, commands, Operators, Keys, Functions, and triggers
  ◦ ACID Properties in DBMS
  ◦ Database Connection SQL to Python
  ◦ SQL vs. NoSQL
• PowerBI
  ◦ Introduction to DAX
  ◦ Data Cardinality and Data Modeling in Power BI Desktop
  ◦ Organization Packs, Security – Working with Others
  ◦ Visualizing Your Data
  ◦ Power BI Dashboards
• Tableau
  ◦ Working with Data using Tableau including Data Extraction and Blending
  ◦ Sorting – Quick Sort, Sort from Headers, Legends, Axis, Tool Bar; Sort by Fields, Nested Sort
  ◦ Forecasting – Exponential Smoothing Technique
  ◦ Hierarchies – Tableau Drill Down and Roll Up Features
  ◦ Tableau – R Integration
  ◦ Data Mining Unsupervised Learning – Clustering
• Excel
  ◦  Hypothesis Testing using Excel
  ◦  Entering and Editing Text and Formulas
  ◦  Excel Functions working with Basics
  ◦  VBA Variables and Operators
  ◦  Formatting Data in an Excel Worksheet
  ◦  Functions: (Text Based, Conditional and Lookup)
  ◦  Pivot Tables
  ◦  Excel Macros
• Python
  Python Data Structures, Dictionaries & Sets
  Python Programming: Web Extraction and Serialization
  Python Packages for Analysing the Data

Course highlights:

• This course is devoted to clinical healthcare data analysis 
• Medical professionals will learn to interpret predictive modelling and EHR reports after this course
• Be associated with our alumni at Capgemini, Dell, Cognizant and much more
• Get your profile reviewed and supported with unlimited mock interviews and quiz sessions 

Connect 360DigiTMG

• Phone: +91-9989994319
• Email: enquiry@360digitmg.com
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6. Data Analytics Certification Course Training by DataMites

Rating:4.8/5 

Placement assistance: Yes

Certification available: Yes

Course duration:  200+ Hours or 6 Months

Price: ₹ 60,900

Course type: Technical training program

Teaching mode: Online and Offline

This data analytics course for 6 months is a no-code one. This will help you to grasp your knowledge of Excel, Tableau, MySQL, and PowerBI. One client or live project is offered with an internship experience certificate upon course completion. 

This course features job assistance, resume preparation, and boosting of skills. IABAC® certification will provide global recognition of skills and open up new opportunities. 

Topics covered in this course:

• Data Analysis Foundation 
• Database: SQL And Mongodb
• Version Control With Git
• Python Foundation
• Data Science Foundation
• Data Analysis Associate
• Artificial Intelligence Foundation
• Advanced data Analytics
• Certified Bi Analyst
• Predictive Analytics With Ml
• Big Data Foundation

Course highlights:

• DataMites help build your career from scratch and assist you in your learning process
• Personalized career guidance from expert counsellors
• Case studies to improve your practical decision-making
• Specialized syllabus as per your profession

Connect DataMites

• Phone: 1800-313-3434
• Email: info@datamites.com
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7. Data Analytics Course Training by LearnBay

Rating: 4.6/5

Placement assistance: Yes

Certification available: Yes

Course duration: 180+ Hours or 9 Months

Price: ₹ 93,220

Course type: Technical training program

Teaching mode: Online 

This data analytics course is provided by Learnbay. Working professionals with less than a year of experience in your career can enroll to develop your career path. Financing as low as 10816 per month is available for students. Exclusive hackathons are arranged by experts through multiple coding competitions. You can master trending analytical tools as per your customization and career needs. 

Topics covered in this course:

• Machine Learning
  ◦  K Nearest Neighbours Model
  ◦  Support Vector Machine(SVM)
  ◦  Logistic Regression Model
  ◦  Hyperparameter Tuning
  ◦  Principal Component Analysis(PCA)
  ◦  Random Forest Model
  ◦  K Means and Hierarchical Clustering
  ◦  Naive Baye’s Model
• Python Programming
  ◦  Strings, Decisions & Loop Control
  ◦  File I/O An d Exceptional Handling and Regular Expression
  ◦  Data Analysis Using Pandas and  Numpy
  ◦  Python Data Types
  ◦  Functions And Modules
  ◦  Data Visualization using Seaborn and  Matplotlib
• MongoDB
  ◦ Introduction to MongoDB and MongoDB (Advance)
• SQL
  ◦  JSON Data & CRUD
  ◦  NoSQL, HBase & MongoDB
  ◦  SQL and RDBMS
  ◦  Programming with SQL
• Excel
  ◦  Using Excel Toolbars: Hiding, Displaying and Moving Toolbars
  ◦  Entering Date Values and using AutoComplete
  ◦  Changing a Chart Type and Working with Pie Charts
  ◦  Data Analysis & Pivot Tables
• Time Series
  ◦ Time Series Forecasting and ARIMA Models
• Big Data & Sparks Analytics
• Power BI
• Tableau

Course highlights:

• Premium mentoring from product-based company experts
• Get hands-on experience in real-world projects directly from relevant companies
• Learn about cohort orientation, languages, deep learning, and programming by enrolling in this course
• The program is suited for fresher professionals looking to upskill their career path 

Connect LearnBay

• Phone: +91 7795687988
• Email: contacts@learnbay.co
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8. Data Analyst Certification Course by Edureka

Rating: 4.3/5

Placement assistance: Yes

Certification available: Yes

Course duration: 250+ Hours

Price: ₹ 59,999

Course type: Masters Technical training program

Teaching mode: Online

This data analytics course by Edureka is suited for expert professionals and freshers. This will help you to enhance your programming skills for building algorithms and gaining in-depth knowledge about structured and unstructured data. 

You can choose free elective courses along with your learning path. Avail the chance to get hands-on training on capstone projects for managing supply chains and sales of companies. 

Topics covered in this course:

• Microsoft Power BI
  ◦  Data Analysis Expressions (DAX)
  ◦ Data Visualization
  ◦  Power BI Report Server
  ◦  R & Python in Power BI
  ◦  Data Visualization
• Statistics Essentials for Analytics
  ◦  Probability and its uses
  ◦  Data Clustering
  ◦  Testing the Data
  ◦  Statistical Inference
  ◦  Regression Modelling
• Tableau
  ◦  Data Connection with Tableau Desktop
  ◦  Calculations in Tableau
  ◦  Geographic Visualizations in Tableau
  ◦  Advanced Charts in Tableau
  ◦  Level Of Detail (LOD) Expressions in Tableau
  ◦  Exploring Tableau Online
• Data Analytics with R Programming
  ◦  Data Visualization, Data Manipulation and Data Import Techniques in R
  ◦  Data Mining: Association Rule Mining and collaborative filtering
  ◦  Linear and Logistic Regression 
  ◦  Data Mining: Clustering Techniques
  ◦  Anova and Sentiment Analysis
  ◦  Data Mining: Decision Trees and Random Forest

Course highlights:

• Get a certificate from Edureka on course completion
• You can never miss a class as you can switch to other batches depending upon the availability of the schedule
• Get lifetime access to course modules and 24*7 support 
• This is a master’s program where you can specialize in two spe

Connect Edureka

• Phone: +91 81474 32266
• Email: sales@edureka.co
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9. PG Data Analyst Course by Data Trained

Rating: 4.2/5

Placement assistance: YES

Certification available: YES

Course duration: 4 Months

Price: NA

Course type: Technical training program/ PG/UG

Teaching mode: Online and Offline/Online/Offline

This data analytics course is aligned with competency standards developed by SSC NASSCOM. This course is in collaboration with industry and has been approved by the Government of India. 

This PG program in data science, machine learning, and neural networks will help you get hands-on training. The affordable course fee structure available in Hyderabad, along with exquisite training and placement guarantee, is also a bonus. 

Topics covered in this course:

• Introduction to learning management system
• Software installation guidance
• Fundamentals of Excel
• Fundamentals of statistics 
• Fundamentals of programming
• Basic coding
• Introduction to different algorithms, flowcharts and pseudocodes 

Course highlights:

• 100% placement guarantee upon course completion
• Live internship provided for 6 months to boost your practical knowledge 
• 6 unique specializations are offered in this course
• Get help from 40+ projects and case studies in this data analytics program

Connect [company name]

• Phone: +91 9560084091
• Email: admissions@datatrained.com
• Facebook
• Twitter
• Linkedin

10. Data Analytics Course Training by SKILL SLASH

Rating: 4.7/5

Placement assistance: Yes 

Certification available: Yes

Course duration: 8 Months

Price: ₹ 60,000

Course type: PG and Graduation

Teaching mode: Online

This live project-based learning has been partnered with tech companies and powered by Microsoft. Dual certification is offered in this data analytics course with the help of live interactive sessions. 

Real-world projects are one of the features that will provide more career prospects. You can build your course under the supervision of a counsellor. Guaranteed job referrals are offered at top companies or startups upon the completion of this course. 

Topics covered in this course:

• Basics of programming and statistics.
• Python, Machine Learning, Applied statistics, and Time series analysis
• SQL, NOSQL, and Case studies
• Advanced Excel and PowerBI
• MongoDB and Tableau 

Course highlights:

• Professionals with at least one year of experience can enroll in this course
• Microsoft certification will help you to be certified in Azure AI Fundamentals
• Real edge experience gained from real-world projects 
• 15+ industry projects along with lifetime access to course materials

Connect SKILL SLASH

• Phone: +91 8391911911
• Email: info@skillslash.com
• Facebook
• Twitter
• Linkedin

11. Data Analytics Course by CEDLEARN

Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course duration: 14 Weeks

Price: ₹35,000 for Online Training, ₹45,000 for Classroom Training

Course type: Technical training program

Teaching mode: Online and Offline

This data analytics course in Hyderabad will help you to learn skills in statistical modeling. This will also boost your knowledge about tools and visualization for extracting useful information from structured or unstructured data sets. 

Learn about Jupyter, MySQL, Power BI, and Excel, among many others. Get engaged with a hybrid learning model and get job placement upon course completion. You can join regular or weekend batches and gain a certificate at the end. 

Topics covered in this course:

• Business Statistics
  ◦  Measures of Central Tendency and dispersion
  ◦  Quality Analysis & Variability 
  ◦  Probability & Distributions
  ◦  Parametric & Non-Parametric Tests
  ◦  Probability & Distributions 
  ◦  Hypothesis Testing & Type I, Type II Errors
  ◦  Sampling Techniques, Estimation Types
• Exploratory Data Analysis
  ◦  Qualitative & Quantitative Techniques
  ◦  Correlation & Covariance Matrices
  ◦  Univariate, Bivariate, & Multivariate
  ◦  Feature Engineering & Extraction
  ◦  Inferential Statistics: t, f, z, ANOVA, Chi-Square
• Business Intelligence
  ◦  Power BI & Analytics Understanding visualization with Tableau
  ◦  Business Intelligence Vs Business Analytics 
  ◦  Getting comfortable with MySQL 
• Data Visualization & Reporting
  ◦  Data Visualisation & Concepts
  ◦  Types of Charts & Word Cloud
  ◦  Visualising Data Infographics
  ◦  Evaluating an Analytics Report
• Advanced Excel for Analytics
  ◦  Functions and formulas to Organise Data
  ◦  Data Analysis Tool paMacros, Power Map & Power Pivot
  ◦  Numerical Analysis – Statistical Functions, Pivot Tables

Course highlights:

• Job-ready program involving no coding skills
• Minimum batch sizes in both regular and weekend courses will help to gain more attention and guidance from mentors
• Internships and projects available to boost your skills
• Work on real business problems and assess your scholarships to get more advantage in the fee payment 

Connect CEDLEARN

• Phone: 08977944952
• Email: hello@cedlearn.com
• Facebook
• Linkedin

12. Data analytics Course by Edvancer Eduventures

Rating: 4.8

Placement assistance: Yes

Certification available: Yes

Course duration: 90 Hours

Price:  ₹ 24,995

Course type: Technical training program

Teaching mode: Online 

This is a certified data analytics program for specialists which will help to increase your salary by 40-100%. No technical background is required while enrolling in this course. 

You can become an expert in predictive modelling, Data visualization and different techniques of data analysis using tools like R, tableau and SQL. This course is self-paced and is supported by industry experts with 70% practical content to make you industry-ready. 

Topics covered in this course:

• Business Analytics in R
  ◦  Data Cleaning & Visualization in R
  ◦  Fundamentals of R
  ◦  Logistic and Linear Regression in R
  ◦  Segmentation for marketing analytics in R
• Data Visualization in Tableau
  ◦  Introduction to BI, Visualization & Tableau
  ◦  Tableau Generated Fields
  ◦  Data Manipulation & Customization
  ◦  Geographical Analysis & Maps
  ◦  Random Forest & XGBoost in R
  ◦  Using Parameters & adding statistics
  ◦  Time series forecasting in R
  ◦  Decision Trees in R
• Data Analysis in SQL
  ◦  SQL data types & operators
  ◦  Aggregating Data in SQL
  ◦  DML and DDL statements in SQL
  ◦  Functions and subqueries in SQL

Course highlights:

• No technical or maths background required for enrolling in this course
• Industry recognized certificate from Edvancer 
• Top class faculty from companies like Fractal, EY and Accenture
• Students placed in Deloitte, Accenture, PWC and more

Connect Edvancer Eduventures

• Phone: +91 8080928948
• Email: info@edvancer.in
• Facebook
• Twitter
• Linkedin

13. Data Analyst Course Training by QuickXpert Infotech

Rating: 4.3

Placement assistance: Yes

Certification available: Yes

Course duration: 4 Months

Price: NA

Course type: Technical training program

Teaching mode: Online 

This data analytics course helps you to learn from SQL to the advanced data analytics tools preferred by the industry. Both freshers and experienced can enroll in this course to become a data analyst professional. 

Real-time projects will be covered as part of the data analytics training provided in this course. Learn about Matplotlib, Seaborn, and NumPy, along with basic Python, MySQL, and Tableau. 

Topics covered in this course:

• Python & Python Analytics
  ◦  OOPs Programming
  ◦  MySQL Server Setup
  ◦  Data Visualization and Data Analytics in Python
  ◦  Database Integration with Python
  ◦  Web Scrapping
  ◦  Database Integration with Python
• SQL
  ◦  Analytic (Window) Functions
  ◦  Grouping functions – AVG, MIN, MAX, COUNT, DISTINCT COUNT, etc.
  ◦  Oracle 18/21c Installation
  ◦  Filters, Sorting, Functions, SET Operators and joins
  ◦  Transactions ( T SQL)
  ◦  Foreign Keys 
  ◦  DML operations 
  ◦  ROWID & ROWNUM 
  ◦  TOP N Analysis or Complex Inline View 
  ◦  DDL
• Tableau
  ◦  Date Aggregations and Date parts
  ◦  Data Visualization and Formatting
  ◦  Chart Types
  ◦  Dashboard
  ◦  Filters 
  ◦  Advanced Functionalities
• Power BI
  ◦  Getting and Transforming Data with Power BI Desktop
  ◦  Modeling with Power BI
  ◦  Introduction to Power BI Service
  ◦  Introduction to DAX
  ◦  Visualising Data with Reports
  ◦  Power BI Gateway and Refreshing Datasets
• Excel Analytics
  ◦  Excel Common Functions
  ◦  Fetching Data From Database
  ◦  Pivot Tables and  Charts
  ◦  Project on Dashboards / Data Visualization

Course highlights:

• Get training from industry-level experts with a curriculum focusing on 80% practical knowledge
• Personal attention is provided to all students along with career counseling
• Reasonable fees and a 100% job-oriented program
• 1000s have already trained and get a chance to join the network of 1000+ companies

Connect QuickXpert Infotech

• Phone: +91-7506252588,
• WhatsApp: +91 7276681665
• Email: inquiry@quickxpertinfotech.com
• Facebook
• Twitter
• Linkedin

Compare the key details of these courses in the following table:

What is the data analytics course fee in Hyderabad? 

The average course fee for a data analytics course in Hyderabad is around ₹50,000. 

However, based on factors such as the institution, course duration, course content, and so on; the course fee can range between ₹ 25,000 to ₹2 lakhs. 

What is the salary of a data analyst in Hyderabad? 

The average salary of a junior data analyst in Hyderabad is around ₹5.8 LPA, but you can expect it to range anywhere between ₹1.8 to ₹ 10 LPA. 

On the other hand, senior data analysts can easily expect to earn ₹ 7 LPA, which can go up to ₹ 17 LPA.

This is a significant amount looking at the average household expense in Hyderabad, and you can expect to live a very comfortable life with it. What is the career scope in data analytics in Hyderabad?

Data analysis is an emerging field, and companies of different sizes and industries are actively hiring data analysts. According to LinkedIn jobs, there are over 3000+ active job openings for the role of data analyst in Hyderabad. 

Learn about the career paths to become a data engineer.

Which data analytics course to pick in 2024? 

Choosing a suitable data analytics course is very up close and personal. But we have still categorized the courses based on budget, intent, and level of knowledge, so you can pick the one that suits your needs. 

• Best course under budget: Data Analytics Course by CEDLEARN
• Best beginner-friendly course: Data Analytics Course by Intellipaat
• Best course for job aspirants:  Data Analyst Course by NXTWave Intensive 2.0

In this listicle post, I will simplify the options for data science courses in Mangalore, addressing common challenges and helping you make the right choices to kickstart your tech journey.

Why do you think we’re credible? Our list is objective, and the ranks are determined only by measures such as

• Placement assistance
• Course fees
• Brand rating
• Number of reviews
• Curriculum

So, you can select the best course to invest in.

Here are the Mangalore data analytics courses at a glance:

1. Datamites: Data science course
2. Zephyr Technologies & Solutions: Data science course
3. Skillslash: Data science course
4. QuickXpert Infotech: Data science training
5. 360DigiTMG: Data science certification
6. St. Aloysius College AIMIT: MSc Data Science course
7. Sahyadri College Engineering: Data science
8. Internshala: Data Science Beginner Course

1. Data Science Course Training by Datamites

Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 8 Months

Price: ₹65,455(online) and ₹74,955(classroom)

Course type: Post-Graduate program

Teaching mode: online and offline

Datamites is Recognized by IABAC (International Association of Business Analytics Certifications). 

Datamites data science program teaches you to use data tools, draw conclusions, and produce helpful business charts. This comprehensive program includes nine courses that cover Python, statistics, and more. It is ideal for data scientists looking to advance their careers.

It is an inclusive course, open to anyone, regardless of their experience level.

Module covered in this course:

• Linear and Logistic Regression, KNN, SVM, ANN in Machine Learning Algorithm
• Big Data : HDFS, KAFKA, Spark- ML/SQL
• Database: Structured Query Language (SQL) and MongoDB
• Business Intelligence (BI) with Power BI and Tableau
• Python Functions with Numpy and Pandas package
• Tensorflow, NLP and CNN in AI
• Git Version Control and GitHub
• Advanced-Data Science with Time Series Forecasting – Arima, MS-Excel, AWS and Azure 

Course highlights:

• It is accredited by IABAC for industry recognition.
• Project mentoring, resume support, and mock interviews for job readiness.
• Resume support and mock interviews for career readiness.
• Industry exposure through live projects from global AI and ML solution providers
• Access to the latest job updates and opportunities.

Connect Datamites

• Phone: 1800 313 3434
• Email:  info@datamites.com
• Facebook
• Twitter
• LinkedIn

2. Data Science Course by Zephyr Technologies & Solutions

Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course duration: 200+ Hours or 3+ Months

Price: NA

Course type: Post-Graduate program

Teaching mode: online and offline

Zephyr offers certification training in data science with AI & ML. The comprehensive course covers all the key aspects of data science with AI & ML.

The trainers also provide personalized guidance and assistance to candidates to help them understand the subject better. 

Who can apply: Diplomas, graduates, and postgraduates can apply for it.

Module covered in this course:

• Mathematical and Statistical Skills
• Machine Learning and their algorithm 
• Data: Warehousing, Mining, Structure and Visualization
• Artificial Intelligence (AI) and Coding
• Deep learning, SQL, R, Python, Prediction Algorithms
• Cloud and Scientific Computing
• Scholastic Model

Course highlights:

• A total of 200+ hours of Applied Learning
• One-on-one mentoring with industry professionals
• More than 50 industry projects and case studies to learn from
• A 100% placement guarantee
• Designed for both working professionals and freshers

Connect Zephyr Technologies & Solutions

• Phone: +91 8111843307
• Email: mail@zephyrtechnologies.co
• Facebook
• Twitter
• LinkedIn

3. Data Science Course by SkillSlash

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 9 Months

Price: ₹65,000

Course type: Technical training program

Teaching mode: online and offline

This course by SKILLSLASH is designed for both beginners and professionals, featuring hands-on training, live sessions, and Microsoft certifications. Whether you are shifting careers or upskilling, this course is your ticket to enter the world of data science.

This course offers you industry-recognized Certification, hands-on experience, flexible learning, and job prospects. Above all, they provide an easy pay option through the EMI facility.

Module covered in this course:

• Programming Essentials
  • Numpy, Pandas, Data-types and Modules in Python
  • File I/O And Exceptional Handling
  • Strings, Decisions, and Conditional Loops
• Statistics
  • Fundamentals of Math and Probability and Linear Algebra
  • Hypothesis Testing Applications
• Machine Learning
  • Principal Component Analysis(PCA)
  • K-Nearest Neighbors Algorithm (KNN), Clustering – K means and Hyperparameter Tuning
  • Advanced Regression Models, Time-Series and Random Forest model
• Tools: Power BI, Excel, SQL, MongoDB and Tableau
• Deployment: AWS, GCP and Azure
• Big data: Hadoop and Spark

Course highlights:

• Dual Certification: Microsoft and real-world work experience certificate from top MNCs/startups.
• Live, stimulating interviews to prepare you for interviews.
• Practical experience with 15+ industry projects in 6+ domains.
• Hybrid course model (online or offline, according to your convenience). Unlimited access to these data science training sessions.
• After completing data science projects, Skillslash provides a project completion certificate.

Connect SkillSlash

• Phone: +91 8391911911
• Email: info@skillsash.com
• Facebook
• Twitter
• LinkedIn

4. Data Science Course Training by QuickXpert Infotech

Rating: 4.3/5

Placement assistance: Yes

Certification available: Yes

Course duration: 3+ Months

Price: NA

Course type: Technical training program

Teaching mode: online 

QuickXpert Infotech is known for Quality Training at Reasonable Fees as they offer customized training packages such as:

• Package 1: Data science 
• Package 2: Data science & data analytics

This course covers everything you need to learn to land a job as a Data Scientist, Machine Learning Engineer, Data Analyst, etc.

With an online & offline mode, it is easy for beginner or professional upskilling to choose based on preferences.

Module covered in this course:

• Python and Python analytics
  • OOPs Programming, MySQL Server Setup, Web Scraping and Data Visualization
• Structured Query Language (SQL)
  • DML operations, Foreign Keys, DDL, Analytic Functions and TOP N Analysis
• Data Analysis and Machine Learning (ML)
  • Time Series Forecasting
  • Supervised and Unsupervised Learning
  • Model Improvement, Metrics, Methods and Validation
• Artificial Intelligence (AI)
  • Deep Learning in Python
  • NLTK and CNN
  • Neural Networks
• Tableau
  • Date Aggregations and Date parts, Chart types, Data Formatting, Filters, etc.

Course highlights:

• Opportunity to place with 1000+ companies.
• 80% practical approach to work on online projects or case studies
• Affordable course fee
• Customized training available

Connect QuickXpert Infotech

• Phone: +91 7506252588
• Email: inquiry@quickxpertinfotech.com
• Facebook
• LinkedIn

5. Data Science Certification Course Training by 360DigiTMG

Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 150+ Hours

Price: ₹55,000

Course type: Technical training program

Teaching mode: online 

360 Digi TMG offers data science course training in Mangalore. In collaboration with the State University of New York, this course provides an advanced understanding of Data Science. You will receive industry masterclasses from experts with over 20 years of experience and cover a range of topics like PySpark, GitHub, ML on Cloud, Python, Facebook Prophet, MLOps, data engineering, and IBM Watson.

With a 96% placement record and a 98% program satisfaction rate, this course equips you with the skills needed to excel in the field of Data Science. 

Whether you’re an IT engineer, data professional, business analyst, or someone looking for a career change, this program is suitable for you.

Module covered in this course:

• Supervised and Unsupervised  Learning in Data Mining
• Python Programming and Associated Packages
• Time Series Forecasting
• Recurrent Neural Network (RNN), Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) 
• Structured Query Languages (SQL) 
• Preliminaries for Data Science
• Power BI

Course highlights:

• Lifetime LMS access.
• Live Free Webinars with unlimited Mock Interviews and Quiz Sessions
• Complementary Courses.
• 24/7 support.
• 120 Hrs to work on 2 live projects.

Connect 360DigiTMG

• Phone: +91 9989994319
• Email: enquiry@360digitmg.com
• Facebook
• Twitter
• LinkedIn

6. M.Sc Data Science Course by St. Aloysius College Institute of Management and IT (AIMIT)

Rating: 4.3/5

Placement assistance: Yes

Certification available: Yes

Course duration: 2 Years

Price: ₹. 1,35,000

Course type: Post-Graduation program

Teaching mode: offline

The MSc in Data Science program at St Aloysius College (Autonomous), Mangalore, is ideal for those who are willing to pursue a postgraduate degree in data science or statistical analysis and want to become data scientists.

Learning outcomes of this course include data analysis, database design and management, use of mathematical and statistical models, and effective data interpretation and communication.

The program covers concepts related to various roles, including Data Scientist, Data Administrator, Data Analyst, Business Analyst, Analytics Manager, Data Architect, and more.

Module covered in this course:

• 1st Semester
  • Statistics and Mathematics for Data Science
  • Data Mining and Warehouse 
  • Big Data and Data Management
  • Algorithms for Advanced Data Analytics
• 2nd Semester
  • Machine Learning Algorithm with  ML using Lab 
  • Multivariate Techniques for Data Science
• 3rd Semester
  • Computational Intelligence and Deep Learning
  • Internet of Things (IOT)
  • Probability and Stochastic Process Models
  • Times Series Forecasting
  • Python for Data Science
  • Modeling, Simulation and Data Science
  • Big Data Analytics with Scala and Spark
  • NoSQL, MapReduce with Hadoop
  • Data Visualization using Tableau

Course highlights:

• State-of-the-art campus for Information Technology Studies
• Access to the latest e-journals and e-books through IEEE, ACM, Safari Books, etc.
• 24×7 Wi-Fi availability in classrooms, campus, and hostels
• Internships in companies and research institutions
• National-level IT fests, IT exhibitions, International Conference etc.
• Participation in international/national seminars, conferences, and paper publications.

Connect AIMIT

• Phone: +91 9141201851 / 52
• Email: admissions@staloysius.ac.in
• Facebook
• Twitter
• LinkedIn

7. Data science department at Sahyadri College Engineering and Management

Rating: 4.3/5

Placement assistance: Yes

Certification available: Yes

Course duration: 4 years for regular students and 3 years  for lateral entry

Price: ₹2,24,000

Course type: Under-graduate program

Teaching mode: offline

The Sahyadri College offers a course in Data Science, an industry-driven program tailored to meet the needs of students pursuing Computer Science and Engineering with a specialization in Data Science (CSE Data Science).

This course teaches practical skills for the real world, preparing students for the ever-changing aata science field and opening doors to careers like Data Scientists, Analysts, Machine Learning Engineers, and Software Developers in various industries like finance, business, economics, and healthcare.

Module covered in this course:

• Supervised and Unsupervised  Learning in Data Mining
• Python Programming and Associated Packages
• Time Series Forecasting
• Recurrent Neural Network (RNN), Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) 
• Structured Query Languages (SQL) 
• Preliminaries for Data Science
• Power BI

Course highlights:

• Entrepreneurship encouragement.
• Major, minor, and specialization options: Part of the four-year program.
• Flexibility for students to choose elective courses.
• Student-centred pedagogy.
• The curriculum focused on recent trends.

Connect 360DigiTMG

• Phone: +91 9989994319
• Email: enquiry@360digitmg.com
• Facebook
• Twitter
• LinkedIn

8.Data Science Beginner Course by Internshala trainings

Rating: 4.5/5

Placement assistance: Yes

Certification available: Yes

Course duration: 6 weeks

Price: ₹1,349

Course type: Technical training program

Teaching mode: online

Internshala Data Science course in Mangalore helps you master the building blocks of Data Science – Python, Statistics, and Predictive Modeling. Over a hundred thousand businesses have put their faith in the Internshala Training certificate. Anyone interested in learning more about data science will find this course to be a great starting point because of the low cost involved.

Topics covered in this course:

• Data Science using Python
  • Understanding Standard Libraries and CSV Files in Python 
  • Variables and Data Types
  • Looping Constructs, Functions, Data Structure, etc.
• Statistics for Data Science
  • Measures of Central Tendency 1 and 2, Central Limit Theorem and Normal Distribution 1 and 2
  • Probability
  • Inferential Statistics
  • Hypothesis Testing
  • Chi-Squared Tests
• Predictive Modeling and Basics of Machine Learning
  • Hypothesis Generation
  • Linear and Logistic Regression
  • K-Means Clustering
  • Univariate Analysis: Continuous and Categorical Variables

Course highlights:

• Beginner-friendly, no prerequisites.
• Doubt clearing through Q&A forum.
• Flexible schedule to learn at your own pace
• Get to work on 2 hands-on projects.
• Cost-effective.

Connect Internshala training

• Phone: +91 8448444851
• Email: trainings@internshala.com
• Facebook
• Twitter
• LinkedIn

The table is created based on the above listing for Data Analytics Courses in Mangalore, comparing key details

What is the average data science course fee in Mangalore? 

Data science courses in Mangalore range anywhere between ₹60,000 to ₹ 2,00,000 based on the type of course you choose.

However, the price majorly depends on how detailed the course is based on factors like online/offline, course curriculum, job placement, live training, etc.

Recommended Read: If you are looking to pursue a career in Data Science, do check this article on How to Start a Career in Data Science in 2023.

What is the salary of a data analyst in Mangalore?

The average annual salary of data analysts in Mangalore is around ₹7.1 LPA. However, Based on technical skills and experience levels, it can range anywhere between ₹1.5 LPA to ₹8 LPA.

Some of the high-paying industries for data analysts in Mangalore are:

• Financial Services
• IT services & Consulting
• BPO
• Sports & Recreations.

Suggested Read: This article provided insights on Types Of Data Science Jobs (With Job Responsibilities). 

What is the career scope of a data analyst in Mangalore? 

In Mangalore, The career prospects for data analysts are promising, aligning with global trends in the data analytics field.

Interest in the role of “Data Analyst’ has seen explosive growth, with a 211% increase in job searches over the past year in the field of data science.

Some interesting statistics that highlight a strong market demand for the data analyst’s career:

• The global data analytics market is projected to reach $745.15 billion by 2030.
• 56% of data leaders planning budget increases, indicating substantial job opportunities.
• Potential creation of 1.4 million new data analytics jobs between 2023 and 2027.
• LinkedIn search shows 1,110+ available jobs in data analyst roles alone in India.

Which Data Science course to follow in 2023 in Mangalore? 

Picking the right course can be challenging. It all depends on your budget, schedule, whether you prefer online or in-person learning and the level of the program you’re aiming for. 

I made it easy for you. Here are our top choices in different categories.

Considering a data science course? Read Data science career paths for insights into potential careers in the field.

Then your wait is over, as we have brought you the ULTIMATE list of top data analytics courses you can find in Indore. 

What makes you believe us? Well, our list is unbiased, and the rankings are completely based on metrics such as:

• Placement assistance
• Course fees
• Brand rating
• Number of reviews
• Curriculum

So, you can select the best course to invest in.

Top data analytics courses in Indore at a glance

1. Excelr: Data Analyst Certification Course
2. IntelliPaat: Data Analytics Course
3. 360DigiTMG: Data Analytics Program
4. Intensive 2.0:Data Analyst Course
5. QuickXpert Infotech: Data Analytics Course
6. SevenMentor: Data Analyst certification
7. Datamites: Data Analytics Course
8. IOTA Academy: Data Analytics Training Course
9. Codersdaily: Data Analytics Course
10. 4Achievers: Data Analytics Program
11. KnowledgeHut: Big Data Analytics Course
12. Henry Harvin: Data Analytics Certifications
13. ACTE: Data Analytics Course

1. Data Analytics Certification Training Course by EXCELR

Rating: 4.5/5

Placement assistance: Yes

Certification available: Yes

Course duration: 150+ Hours or 6 Months

Price: ₹44999

Course type: Technical training program

Teaching mode: Online 

The data analyst course offered by ExcelR will help you to secure your dream job. Learn about Tableau, Excel, Power BI, MySQL, and more relevant skills for your perfect career choice.

ExcelR has 2000+ hiring partners and offers certificates in collaboration with IBM. Freshers from any stream with a graduation degree can apply to this course. Good analytical and logical skills will be preferred as suited to the market needs. 

Topics covered in this course:

• Excel: Basics to Advanced 
• MySQL 
• Tableau 
• Power BI
• Business Statistics 
• Fundamentals of R 
• Fundamentals of Python 
• SAS
• ChatGPT

Course highlights:

• Top-notch faculty with more than 12 years of industry experience
• Industry-relevant exhaustive course curriculum, as well as real-life projects and boot camps
• Intensive preparation for interviews from the first day
• Learn about Data analysis concepts, Data visualization, Large Language Models, ChatGPT, Python, and R programming with self-paced learning modules

Connect ExcelR

• Phone: +91 96321 56744
• Email: enquiry@excelr.com
• Facebook
• Twitter
• Linkedin

2. Data Analytics Course by Intellipaat

Rating: 4.4/5

Placement assistance: Yes

Certification available: Yes

Course duration: 200 Hours

Price: ₹ 100,035

Course type: Technical training program

Teaching mode: Online 

The data analysis course of Indore by Intellipaat is in collaboration with the Technology Innovation Hub of IIT Madras. This course will help you to master your knowledge and skills in Data Wrangling, Power BI, Data Mining, etc. 

The online course will help you to gain knowledge about different business domains, data transformation and optimization techniques. Also learn about data science, strategies for executive projects and data visualization in depth. 

Topics covered in this course:

• Data wrangling with SQL
• Data Transformation using MS Excel and Python
• Visualization using Power BI
• Statistics and Machine Learning using R Programming
• Predictive Modeling
• Advanced Machine Learning Techniques
• KNIME
• Data Science Capstone Project
• Presto
• Feature Engineering
• Time-Series Forecasting
• Data Science Execution Strategy

Course highlights:

• Become a successful data analyst in seven months and get a certificate from IIT Madras upon completion
• There are no prerequisites before taking this course, basic knowledge will help to understand better
• Learn about prediction algorithms, advanced statistics, SQL, and much more with real-life projects and examples
• No-cost EMI options are available for this course
• Boost your resume and LinkedIn profile

Connect Intellipaat

• Phone: +91-7022374614
• Email: Sales@Intellipaat.Com
• Facebook
• Twitter
• Linkedin

3. Data Analytics Certification Course Training by 360DigiTMG

Rating: 4.8

Placement assistance: Yes

Certification available: Yes

Course duration: 132+ Hours

Price: ₹40,000

Course type: Post Graduate Diploma Certification Program

Teaching mode: Online 

This is a course in collaboration with IBM and fast-track your career in data analytics training. 360DigiTMG offers a training program that helps you be equipped with data processing tools.  

Learn about SQL/NoSQL, Excel, and different data visualization tools for analyzing and presenting visual stories to the end-users. Learn about Data Mining of Structured (RDBMS) and Unstructured (Big Data) data and advanced Excel, too with the help of real-life examples. 

Topics covered in this course:

• Structured Query Language SQL
  ◦ DBMS vs. RDBMS
  ◦ Install PostgreSQL and MySQL
  ◦ SQL -Data Types, commands, Operators, Keys, Functions, and triggers
  ◦ ACID Properties in DBMS
  ◦ Database Connection SQL to Python
  ◦ SQL vs. NoSQL
• PowerBI
  ◦ Introduction to DAX
  ◦ Data Cardinality and Data Modeling in Power BI Desktop
  ◦ Organization Packs, Security – Working with Others
  ◦ Visualizing Your Data
  ◦ Power BI Dashboards
• Tableau
  ◦ Working with Data using Tableau including Data Extraction and Blending
  ◦ Sorting – Quick Sort, Sort from Headers, Legends, Axis, Tool Bar; Sort by Fields, Nested Sort
  ◦ Forecasting – Exponential Smoothing Technique
  ◦ Hierarchies – Tableau Drill Down and Roll Up Features
  ◦ Tableau – R Integration
  ◦ Data Mining Unsupervised Learning – Clustering
• Excel
  ◦  Hypothesis Testing using Excel
  ◦  Entering and Editing Text and Formulas
  ◦  Excel Functions working with Basics
  ◦  VBA Variables and Operators
  ◦  Formatting Data in an Excel Worksheet
  ◦  Functions: (Text Based, Conditional and Lookup)
  ◦  Pivot Tables
  ◦  Excel Macros
• Python
  ◦ Advanced Python Programming
  ◦  Python Data Structures, Dictionaries & Sets
  ◦  Python Programming: Web Extraction and Serialization
  ◦  Python Packages for Analysing the Data

Course highlights:

• 365 days of access to online classes besides 20+ live hours of industry master classes
• Get placed in the data analytics field 
• Complimentary basic courses are also available as per your customization 
• Unlimited mock interviews and hands-on experience in live projects

Connect 360DigiTMG

• Phone: +91-9989994319
• Email: enquiry@360digitmg.com
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4. Data Analyst Course by NxtWave

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 5 Months

Price: ₹45,000 For PostPaid and ₹90,000 For PrePaid

Course type: Technical training program

Teaching mode: Online 

Designed by an industry expert, this data analyst course in Indore helps to gain hands-on experience in real-time projects. Build a comprehensive portfolio and get an industry-recognized certificate to ensure job readiness. 

B.Tech, B.Com, B.sc, and BBA students are encouraged to join this course for 5 months without having any prior coding knowledge. 1500+ companies like Amazon, Microsoft, and more have already hired learners. 

Topics covered in this course:

• Fundamentals
  ◦  Responsive Website Design
  ◦  Static Website Design
  ◦  Introduction to Databases
  ◦  Programming Foundations with Python
  ◦  Bootstrap
• Data Analyst Specialization
  ◦  Data Modelling & DAX
  ◦  Advanced-Data Visualization
  ◦  Data Cleaning and transformation using Excel / Power Query
  ◦  Data Analytics using Tableau
  ◦  Data Visualization
  ◦  Data Analysis using Python Libraries

Course highlights:

• Scholarships up to Rs 16000/- available
• Learn about SQL, Python, descriptive statistics, Data visualization, Data transformation, Dashboard creation, and much more
• This online course includes real-time projects to help build your portfolio
• Unlimited opportunities are offered from a pool of 3000+ companies

Connect NXT WAVE

• Phone: +91 9390111761
• Email: support@nxtwave.tech
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5. Data Analytics Course Training by QuickXpert Infotech

Rating: 4.3

Placement assistance: Yes 

Certification available: Yes

Course duration: 4 Months

Price: NA

Course type: Technical training program

Teaching mode: Online

The data analytics course is offered in online and classroom format at reasonable packages. QuickXpert Infotech offering this course in Indore will help to receive training from experts. 

This is a 100% job-oriented program, and you get a chance to get hired by 1000+ companies. 80% of the coursework is practical to make you adept with real-life business scenarios. A certificate is provided upon course completion, and prepare yourself for interviews with our faculty. 

Topics covered in this course:

• Python & Python Analytics
  ◦  OOPs Programming
  ◦  MySQL Server Setup
  ◦  Data Visualization and Data Analytics in Python
  ◦  Database Integration with Python
• SQL
  ◦  Grouping functions
  ◦  Filters, Sorting, Functions, and SET Operators 
  ◦  Transactions ( T SQL)
  ◦  DML operations 
  ◦  ROWID & ROWNUM 
  ◦  DDL
• Tableau
  ◦  Date Aggregations and Date parts
  ◦  Data Visualization and Formatting
  ◦  Chart Types
  ◦  Advanced Functionalities
• Power BI
  ◦  Getting and Transforming Data with Power BI Desktop
  ◦  Modeling with Power BI
  ◦  Introduction to Power BI Service
  ◦  Introduction to DAX
• Excel Analytics
  ◦  Fetching Data From Database
  ◦  Pivot Tables and  Charts
  ◦  Project on Dashboards / Data Visualization

Course highlights:

• No prerequisites are required for enrolling in this course
• Get 4 months of training for  a data analyst and 6 months for an advanced data analyst
• Gain knowledge about SQL and advanced data analytics tools alongside real-time projects from our experts

Connect QuickXpert Infotech

• Phone: +91-7506252588,
• WhatsApp: +91 7276681665
• Email: inquiry@quickxpertinfotech.com

6. Data Analytics Course by SevenMentor

Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 90+ Hours

Price: NA

Course type: Technical training program

Teaching mode: Online and Offline

The passion of SevenMentor Institute is to provide a one-of-a-kind experience for the students. Certified lecturers are from Amazon, Google, and Microsoft who have significant experience in real business. 

Learn about data science, data analytics, and SQL scripting in depth to make your professional career robust. The data analytics certification can be taken by any freshers and working professionals. The training plan varies on three levels based on your preferences. 

Topics covered in this course:

• MYSQL Database
• Big Data
• Advanced Java and Core Java
• Hadoop, SCALA, MONGODB, Tableau, Python, APACHE SPARK
• R Programming, Advanced Tool for Analysis

Course highlights:

• Regular or weekend batches available for basic, intermediate, and advanced levels
• Certificate of completion can attain leading job posts
• Become proficient in  HIVE, R, Scala, and SQL, or Structured Query Language
• Get practical experience on commercial distributions and Pig Hive Hbase

Connect SevenMentor

• Phone: +91 77980 58777
• Email: support@sevenmentor.com
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7. Data Analytics Certification Course Training in Indore by Datamites

Rating: 4.8/5

Placement assistance: Yes

Certification available: Yes

Course duration: 6 Months or 200+ Hours

Price:  ₹60,900 for Online and ₹65,900 for Classroom

Course type: Technical training program

Teaching mode: Online and Offline

This is a no-coding course offered by Datamites. The entire training will include real-world projects and valuable case studies to boost practical knowledge. IABAC®  having global recognition is provided upon course completion. 

Expert PhD holders and industry trainers are associated with this course. Proper career guidance is provided by expert counselors for career enhancement in managerial roles. A specialized syllabus in cutting-edge technologies is present for managers.

Topics covered in this course:

• Data Analysis, Data Science, AI, and Python Foundation
• Data Analysis Associate 
• Predictive Analytics With Ml 
• Version Control With GIT
• SQL And MongoDB 
• Big Data Foundation 
• Certified BI Analyst 

Course highlights:

• 50,000 candidates already trained by DataMites
• Three-phase learning technique to deliver high-quality training 
• Certified data analyst curriculum offered in online mode
• JainX Data Analytics Certification and the global IABAC certification for learners

Connect Datamites

• Phone: 1800-313-3434
• Email: info@datamites.com
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8. Data Analytics and Placement Training Institute In Indore by IOTA Academy 

Rating: 4.8/5

Placement assistance: Yes 

Certification available: Yes

Course duration: 6 Months

Price: NA

Course type: Technical training program

Teaching mode: Online and Offline

IOTA Academy aims to upskill according to the present job demand. Bridge your academic and professional life with the data analytics and placement training offered by the institute. 

This is a digital, data-driven, and programming-based course for 6 months. Learn about basic maths and statistics besides the data visualization and analytics tools. Learn from industry experts, and more focus is given to real-life projects to enhance practical knowledge. 

Topics covered in this course:

• Data Analytics Introduction to Analytics and Data Analysis 
• Data Visualisation and Analytics Tools: Excel, Tableau/Power BI & SQL 
•  Basic Maths and Statistics 
• Python libraries like Pandas, Numpy, Matplotlib, etc. 
•  Python for Data Analysis 

Course highlights:

• Learn about Python, Excel, Tableau/Power BI & SQL
• Gain skills in exploring Python libraries like Pandas, Numpy, Matplotlib, etc.
• Get placement assistance from Iota Academy
• Get hands-on experience on real-world projects

Connect IOTA Academy

• Phone: +91 78696 64602
• Email: wecare.iota@gmail.com
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9. Data Analytics Training in Indore by CodersDaily

Rating: 4.9/5

Placement assistance: Yes

Certification available: Yes

Course duration: NA

Price: NA

Course type: Technical training program

Teaching mode: Online and Offline

This data analytics course in Indore is provided by Codersdaily. This will help you to upskill your technical knowledge in data analytics development.

The course is available both in online and offline modes pan India. Learn from scratch to an advanced level and get job-ready in the industry. Live classes are offered by data scientists, and 1:1 mentorship from industry veterans. Free placement support is provided along with a certificate of completion.

Topics covered in this course:

• Microsoft Azure
• NumPy
• matplotlib
• Microsoft SQL Server
• Power BI
• Pandas
• Python

Course highlights:

• Live business scenario projects
• Extensive career support from industry leaders
• Freshers from any background with analytical and logical skills can apply
• A free learning resource for a lifetime

Connect [company name]

• Phone: +91 885 999 4143
• Email: info@codersdaily.in
• Facebook

10. Program of Data Analysis Course Training by 4Achivers

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 3 to 6 Months

Price: NA

Course type: Technical training program

Teaching mode: Online and Offline

4achievers offers data analysis courses to students. The course is designed to help develop the skills and knowledge needed to excel in the data analytics field. 100% placement is offered to the candidate along with a job-ready certificate on course completion. 

This is a dedicated course training program having a team of qualified and experienced trainers. Extensive experience in the field enriches the faculty with the knowledge to make you industry-ready. 

Topics covered in this course:

• Perform Statistical analysis
• Identify Data source
• Gather and clean data
• Build Predictive models
• Implement Data-Driven Solutions
• Monitor and Update Analysis
• Communicate Findings and Insights

Course highlights:

• 100% placement assistance
• Global certification available
• Live projects and MOC interview preparation for learners
• Classes available in online and offline modes as per convenience and preference

Connect 4Achivers

• Phone: +91 8010805667
• Email: info@4achievers.com
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11. Big Data Analytics Course Training in Indore by Knowledgehut

Rating: 4.7/5

Placement assistance: Yes

Certification available: Yes

Course duration: 30 Hours

Price: NA

Course type: Technical training program

Teaching mode: Online

30 hours of intensive training on Big data and frameworks by Knowledegehut. Curriculum designed by experts and live classes organized for learner convenience. 

Learn the concepts from scratch and move on to the advanced level with practical knowledge and hands-on experience. No specific requisites for enrolling in this course but logical and analytical knowledge will be preferred for understanding the concepts. 

Topics covered in this course:

• Introducing Big Data & Hadoop
• Data Analytics using Pentaho as an ETL tool
• HDFS (Hadoop Distributed File System)
• Hadoop Installation Modes and HDFS
• Hadoop: Ecosystems, Developer Tasks, Hadoop Daemon Processes

Course highlights:

• Mentoring provided by industry experts
• Get reviews and feedback on final projects from professional developers
• Familiarity with basic programming languages will be beneficial for learners
• Discontinuation of course within first 48 hours of registration is available 

Connect Knowledgehut upGrad

• Phone:+91-84484-45027 
• Email: reachus@knowledgehut.com
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12. Big Data Analytics Certification Course In Indore by HENRY HARVIN

Rating: 4.1/5

Placement assistance: Yes

Certification available: Yes

Course duration: 32 Hours

Price:  ₹29,500

Course type: Post Graduate data analyst program

Teaching mode: Online

Learn about big data technology and advanced analytics techniques from this upskilling and reskilling institute. Henry Harvin Academy has industry experts with more than 15 years of industry experience.

After enrolling, become a member of Elite Analytics Academy of Henry Harvin®. Also, avail of the 1-year gold membership for e-learning access and joining masterclass programs. Learn about Hive Illustration, Hadoop framework, query operations, Apache Kafka, and more. 

Topics covered in this course:

• Hadoop: Master your Big data 
• Hive: Big data SQL Module  
• Advanced Spark
• Apache Kafka – A distributed streaming platform 
• Spark: Stream and analyze the Big Data Module 

Course highlights:

• Learn about Hadoop framework, HDFS and Hadoop 2. x- YARN, MapReduce 
• Weekly 10+ job opportunities offered
• Henry Harvin academy: 3425+ Google Reviews, 1100+ YouTube Testimonials with 4.5+ Rating Rated on GoAbroad, Trustpilot, GoOverseas & more
• Improve your CV and LinkedIn profile with professional enhancement

Connect HENRY HARVIN

• Phone: +91 9891953953
• Email: Hello@henryharvin.com
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13. Big Data Analytics Course by ACTE

Rating: 4.6

Placement assistance: Yes

Certification available: Yes

Course duration: 40+ Hours

Price: NA

Course type: Graduate 

Teaching mode: Online 

ACTE big data analytics certification course in Indore offers fundamental mastery of center standards with an involved approach. Hands-on acquired learning for 40+ hours is available in this course to boost your professional career.

Classroom bach or online training is available for learners as per their preference. 1:1 customized training is provided based on the necessity of the development of the skills according to industry standards. 

Topics covered in this course:

• Module 1
  ◦  Analytical Terminology, Analytical Methodology
  ◦  Reading Data From External Files (.Txt, .Xls, .Csv) -Tasks
  ◦  Data Exploration: ProcGchart, ProcGplot -Tasks
  ◦  Data Exploration: Hypothesis, Types of Errors
  ◦ Data Preparation: Do-Loops, Arrays  and etc
• Module 2
  ◦  Introduction to Regression: ProcCorr, ProcReg
  ◦  Dimensionality Reduction Techniques: Proc Factor
  ◦  Clustering case study (Task) 
  ◦  Association Rules — Introduction and etc
• Module 3
  ◦  Proc Logistic -Case study,( Task)
  ◦  Neural Nets – the Case study
  ◦  Introduction to SVM, Naive Bayes, Case study and etc
• Module 4
  ◦  Proc Arima — Case study (Task)
  ◦  Sentiment Analysis in R ( Case study)
  ◦  Introduction to Text Analytics and Optimization

Course highlights:

• Industry expert faculties who have already completed 500+ batches
• 40 hours course duration helps to learn within a short span
• Free demo class available
• Certification guidance and 100% placement online training provided by ACTE
• Get a chance to be hired by Amazon, Oracle, Microsft, Pearson and more 

Connect ACTE

• Phone: +91-8376 802 119
• Email: contact@acte.in
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What is the data analytics course fee in Indore? 

The average course fee for a data analytics course in Indore is around ₹ 40,000. However, depending on factors like course duration, course certification type, and course content, the price can vary anywhere between ₹ 29K to ₹ 1.5 lakhs. 

What is the salary of a data analyst in Indore? 

The average salary of a data analyst in Indore is around ₹5.4 LPA. but don’t forget that it is for an entry-level junior position role. For senior data analysts, the average salary ranges around ₹ 11 LPA, which is double the amount. 

However, depending on factors such as location or company, you can earn up to ₹ 8 LPA even in an entry-level position. 

What is the career scope in data analytics in Indore?

Data analytics is an emerging field, especially after big data gained popularity. Nowadays, almost every medium to big-size organization looks for data analysts to make more data-driven decisions. 

As you can see on LinkedIn, there are over 40 active job postings for the role of data analyst for Indore’s location. Hence, it is fair to say that across the nation or internationally, the numbers will be much higher. 

Which data analytics course to pick in 2023? 

Picking the right data analytics course can be tricky and is dependent upon various factors like budget, time in hand, or intention all of which are very personal. 

However, to make it easier for you, we have picked the best data analytics course based on different categories. 

• Best Under Budget:  Big Data Analytics Certification Course In Indore by HENRY HARVIN
• Best Beginner Friendly: Data Analytics Certification Course Training by 360DigiTMG
• Best Course For Job Aspirants: Program of Data Analysis Course Training by 4Achivers

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