BCA Course Syllabus: Fees, Duration, & Eligibility

Discover the complete BCA course syllabus for the 2024-2025 academic session in India. This guide comprises all the necessary subjects you need to learn along with the topics covered and the main projects to perform.

 Download BCA course syllabus

In a hurry? Download the complete BCA course syllabus:

• PDF→
• Google Docs→
• Word document→

BCA Course Syllabus and Curriculum 2024

Here’s a BCA course syllabus at a glance:

Module 1: Computer Fundamentals

Basic Concepts of Computers

• Definition of computers
• Types of computers: Personal computers, Workstations, Servers, Mainframes

Hardware Components

• Central Processing Unit (CPU): Functions and types
• Memory: RAM, ROM, Cache Memory
• Storage Devices: Hard Disk Drives (HDD), Solid State Drives (SSD), Optical Drives
• Input Devices: Keyboard, Mouse, Scanner
• Output Devices: Monitor, Printer, Speakers

Software Components

• System Software: Operating systems, Device drivers
• Application Software: Word processors, Spreadsheets, Databases

⭐ Hands-on projects to practice: 

• Build Your Own Computer Specification Guide: Create a comprehensive guide that outlines various computer types, their hardware components, and recommended specifications for different use cases.
• Simple Computer Hardware Inventory System: Develop a basic inventory system to track computer hardware components using a spreadsheet application.

Module 2: Programming Fundamentals

Basic Syntax and Structure

• Structure of a C program
• Compilation process: Preprocessing, Compilation, Linking, and Loading

Data Types and Variables

• Primitive data types: int, float, char, double
• Variable declaration and initialization
• Constants and enumerations

Control Structures

• Conditional statements: if, else, switch
• Looping constructs: for, while, do-while

Functions and Recursion

• Function declaration, definition, and calling
• Parameter passing: by value and by reference
• Recursion: Definition, examples, and use cases

Pointers and Arrays

• Pointer basics: Declaration, initialization, and dereferencing
• Array declaration and manipulation
• Pointer arithmetic and arrays

⭐ Hands-on projects to practice: 

• Simple Calculator: Create a simple calculator application that performs basic arithmetic operations (addition, subtraction, multiplication, and division) using functions and control structures.
• Array and Pointer Manipulation: Create a program that demonstrates the use of arrays and pointers by performing operations such as sorting, searching, and displaying elements.

Module 3: Data Structures

Introduction to Data Structures

• Definition and importance of data structures
• Classification: Linear vs. Non-linear data structures

Arrays, Stacks, and Queues

• Array operations: Insertion, deletion, searching
• Stack: Definition, operations (push, pop), applications (expression evaluation)
• Queue: Definition, operations (enqueue, dequeue), types (circular queue, priority queue)

Linked Lists

• Singly linked lists: Creation, insertion, deletion, traversal
• Doubly linked lists: Advantages, operations, applications

Trees

• Binary trees: Properties, traversal methods (inorder, preorder, postorder)
• Binary search trees: Insertion and deletion operations
• AVL trees and B-trees: Balancing techniques

Graphs

• Graph representations: Adjacency matrix and adjacency list
• Graph traversal algorithms: Breadth-First Search (BFS) and Depth-First Search (DFS)

⭐ Hands-on projects to practice: 

• Linked List Management System: Create a program that implements a singly linked list with functionalities for insertion, deletion, and traversal.
• Binary Search Tree (BST) Operations: A binary search tree (BST) with functionalities for insertion, deletion, and traversal (inorder, preorder, postorder)

Module 4: Mathematics for Computing

Discrete Mathematics

• Sets, relations, and functions
• Combinatorics: Permutations and combinations
• Graph theory: Basics and terminology

Probability and Statistics

• Basic probability concepts: Events, sample space, probability rules
• Descriptive statistics: Mean, median, mode, variance, standard deviation
• Probability distributions: Binomial, Poisson, normal distributions

Linear Algebra Basics

• Vectors and matrices: Definitions and operations
• Matrix operations: Addition, multiplication, determinants, inverses

⭐ Hands-on projects to practice: 

• Probability and Statistics Calculator: Develop a console-based application that performs basic probability and statistical calculations, such as mean, median, mode, variance, and standard deviation.
• Graph Theory Visualization and Shortest Path Algorithm: Create a program that visualizes a graph and implements a shortest path algorithm (e.g., Dijkstra’s algorithm) to find the shortest path between two nodes.

Module 5: Database Management Systems

Introduction to Databases

• Database concepts and types: Relational, NoSQL, Object-oriented
• Database management systems overview: Functions and components

Relational Database Model

• Tables, rows, and columns: Structure of relational databases
• Primary keys and foreign keys: Importance in relational databases

SQL: DDL, DML, and DCL

• Data Definition Language: CREATE, ALTER, DROP
• Data Manipulation Language: SELECT, INSERT, UPDATE, DELETE
• Data Control Language: GRANT, REVOKE

Normalization and Database Design

• Normal forms: 1NF, 2NF, 3NF, BCNF
• Designing Entity-Relationship (ER) diagrams and schemas

Transactions and Concurrency Control

• ACID properties of transactions: Atomicity, Consistency, Isolation, Durability
• Locking mechanisms and isolation levels

⭐ Hands-on projects to practice: 

• Student Database Management System: Create a Student Database Management System (DBMS) that allows for the storage, retrieval, and management of student information using a relational database.
• E-commerce Product Catalog Database: Develop a database for managing an e-commerce product catalog, including products, categories, customers, and orders.
• Implement CRUD Operations: Write SQL queries for the following operations:
  • Create: Add new products, categories, customers, and orders.
  • Read: Retrieve product details, category listings, and customer orders.
  • Update: Update product prices or stock quantities.
  • Delete: Remove a product or category from the catalog.

Module 6: Web Technologies

HTML5

• Structure of HTML documents: Elements, attributes, and nesting
• Semantic elements: Header, footer, article, section
• Forms and input types: Text, radio, checkbox, file uploads
• Multimedia elements: Audio and video integration

CSS3

• Styling web pages: Selectors, properties, and values
• Box model: Margin, border, padding, and content
• Positioning: Static, relative, absolute, fixed
• Responsive design principles: Media queries and flexible layouts

JavaScript

• Basics of JavaScript syntax: Variables, data types, operators
• DOM manipulation: Selecting elements, modifying content and styles
• Event handling: Click, hover, form submission
• AJAX for asynchronous web requests: Fetch API and XMLHttpRequest

Server-Side Scripting

• Introduction to PHP/Node.js: Setting up environments
• Handling form data: GET and POST methods
• Session management: Cookies and session variables
• Database connectivity: CRUD operations with SQL

⭐ Hands-on projects to practice: 

• Personal Portfolio Website: Create a personal portfolio website to showcase your skills, projects, and experiences.
• Online Voting System: Develop a simple online voting system that allows users to cast votes for different candidates.
• Recipe Sharing Platform: Build a recipe-sharing platform where users can submit, view, and search for recipes.

Module 7: Object-Oriented Programming

Principles of OOP

• Concepts: Classes, objects, inheritance, polymorphism
• Encapsulation: Access modifiers and data hiding
• Abstraction: Abstract classes and interfaces

OOP in Java/C++

• Class and object creation: Constructors and destructors
• Method overloading and overriding: Polymorphism in action
• Static and instance members: Differences and usage

Exception Handling

• Types of exceptions: Checked and unchecked exceptions
• Try-catch blocks: Handling exceptions gracefully
• Finally clause: Cleanup actions

File Handling

• Reading from and writing to files: Text and binary files
• File streams: Input and output streams
• Serialization: Object serialization and deserialization

⭐ Hands-on projects to practice:

• Library Management System: Develop a Library Management System that allows users to manage books, members, and borrowing transactions.
• Online Quiz Application: Create an online quiz application that allows users to take quizzes, view results, and manage questions. 
• Personal Finance Tracker: Develop a personal finance tracker that allows users to manage their income and expenses, providing insights into their financial status.

Module 8: Operating Systems

OS Concepts and Types

• Functions of an operating system: Process management, memory management, file system
• Types of operating systems: Batch, time-sharing, real-time, distributed

Process Management

• Process states and transitions: New, ready, running, waiting, terminated
• Scheduling algorithms: First-Come, First-Served (FCFS), Shortest Job First (SJF), Round Robin

Memory Management

• Memory allocation techniques: Contiguous, paging, segmentation
• Virtual memory concepts: Paging and page replacement algorithms

File Systems

• File organization and access methods: Sequential, random, indexed
• File system implementation: File descriptors, directories, and storage management

⭐ Hands-on projects to practice:

• Memory Management Simulator: Develop a memory management simulator that demonstrates different memory allocation techniques such as contiguous allocation, paging, and segmentation. 
• Simple Shell Implementation: Create a simple command-line shell that can execute basic commands, manage processes, and handle input/output redirection.
• File System Simulation: Create a file system simulator that allows users to perform basic file operations such as creating, reading, writing, and deleting files.

Module 9: Computer Networks

Network Architecture and Models

• OSI model: Layers and their functions
• TCP/IP model: Comparison with OSI

Data Link Layer

• Error detection and correction techniques: Parity bits, checksums, CRC
• Multiple access protocols: CSMA/CD, CSMA/CA

Network Layer

• Routing algorithms: Dijkstra’s algorithm, Bellman-Ford algorithm
• IP addressing: IPv4 and IPv6, subnetting

Transport Layer

• TCP vs. UDP: Characteristics and uses
• Flow control and congestion control mechanisms: Sliding window protocol, congestion avoidance

⭐ Hands-on projects to practice: 

• Network Simulation Tool: Create a network simulation tool that allows users to visualize and simulate different network topologies and protocols.
• Simple Chat Application: Develop a simple chat application that uses TCP/IP for communication between clients and a server.
• Packet Sniffer Tool: Create a packet sniffer tool that captures and analyzes network packets in real time.

Module 10: Software Engineering

Software Development Life Cycle (SDLC)

• Phases of SDLC: Requirements, design, implementation, testing, maintenance
• Models: Waterfall, Agile, Spiral, V-Model

Requirements Gathering and Analysis

• Techniques for requirements elicitation: Interviews, surveys, workshops
• Documentation and specification: Use cases, user stories

Design Methodologies

• Architectural design: Client-server, microservices, monolithic
• Object-oriented design principles: UML diagrams (class diagrams, sequence diagrams)

Testing Strategies and Methodologies

• Types of testing: Unit testing, integration testing, system testing, acceptance testing
• Test case design: Black-box testing, white-box testing

⭐ Hands-on projects to practice: 

• Task Management Application: Develop a task management application that allows users to create, manage, and track tasks. This project will cover the entire software development life cycle, from requirements gathering to implementation and testing.
• E-commerce Website: Create a fully functional e-commerce website that allows users to browse products, add items to their cart, and complete purchases. 
• Bug Tracking System: Develop a bug tracking system that allows users to report, track, and manage software bugs. This project will focus on requirements gathering, design, implementation, and testing methodologies.

Module 11: Artificial Intelligence

Introduction to AI

• Definition and history of AI: Turing test, AI winter
• Applications of AI: Natural language processing, robotics, expert systems

Search Algorithms

• Uninformed search strategies: Breadth-First Search (BFS), Depth-First Search (DFS)
• Informed search strategies: A* algorithm, greedy search

Knowledge Representation

• Logic-based representation: Propositional logic, predicate logic
• Ontologies and semantic networks: Hierarchical structures

Machine Learning Basics

• Types of machine learning: Supervised, unsupervised, reinforcement learning
• Common algorithms: Linear regression, decision trees, k-means clustering

⭐ Hands-on projects to practice: 

• AI-Powered Chatbot: Develop a simple AI-powered chatbot that can engage in basic conversations and answer user queries using natural language processing (NLP).
• Pathfinding Visualizer: Create a pathfinding visualizer that demonstrates various search algorithms (e.g., BFS, DFS, A*) on a grid.
• Machine Learning Model for House Price Prediction: Develop a machine learning model that predicts house prices based on various features (e.g., size, location, number of rooms).

Module 12: Electives (Choose Based on Interest)

Elective 1: Cloud Computing

Cloud Service Models

• Understanding IaaS, PaaS, SaaS: Definitions and examples
• Advantages and challenges of cloud computing

Cloud Deployment Models

• Public, private, and hybrid clouds: Characteristics and use cases
• Cloud service providers overview: AWS, Azure, Google Cloud

Introduction to Cloud Technologies

• Cloud storage solutions: S3, Google Drive
• Cloud security best practices: Identity management, data encryption

⭐ Hands-on projects to practice: 

• Cloud-Based Document Collaboration System: Build a collaborative document editing system that allows multiple users to work on documents simultaneously.
• Serverless Image Processing Application: Create a serverless application that processes images uploaded by users.

Elective 2: Big Data Analytics

Big Data Concepts and Challenges

• Definition of big data: Volume, velocity, variety
• Challenges in big data processing: Data quality, privacy, and security

Hadoop Ecosystem

• Introduction to Hadoop: HDFS, MapReduce
• Tools in the Hadoop ecosystem: Hive, Pig, HBase

Data Mining and Machine Learning Techniques

• Data preprocessing: Cleaning, transforming, and normalizing data
• Common data mining algorithms: Association rules, clustering, classification

⭐ Hands-on projects to practice: 

• Real-Time Data Processing: Develop a system that collects, processes, and visualizes streaming data in real time.
• Predictive Analytics with Machine Learning: Build a predictive analytics application that forecasts future trends based on historical data.

Elective 3: Mobile Application Development

Android/iOS Development Basics

• Setting up development environments: Android Studio, Xcode
• Understanding app architecture and lifecycle

User Interface Design and Navigation

• Layouts, views, and UI components: RecyclerView, Fragments
• Navigation patterns: Intents, Navigation components

Data Storage and Retrieval

• Local storage options: SQLite, Shared Preferences
• Remote data handling: APIs and web services

⭐ Hands-on projects to practice: 

• Expense Tracker App: Create a mobile application that helps users track their expenses and manage budgets.
• Fitness Tracker App: Develop a mobile application that tracks user workouts and fitness goals.

Elective 4: Cyber Security

Introduction to Cybersecurity Principles

• Importance of cybersecurity in the digital age
• Common threats: Malware, phishing, denial of service attacks

Network Security

• Firewalls, intrusion detection systems (IDS)
• VPNs and secure communication protocols: SSL/TLS

Cryptography Basics

• Symmetric vs. asymmetric encryption: AES, RSA
• Hashing algorithms: SHA-256, MD5

⭐ Hands-on projects to practice: 

• Secure File Transfer Application: Build an application that securely transfers files over the internet using encryption.
• Intrusion Detection System (IDS): Develop a basic IDS that monitors network traffic for suspicious activity.

Elective 5: Data Science

Data Preprocessing and Cleaning

• Techniques for handling missing data: Imputation, removal
• Data transformation: Normalization, standardization

Exploratory Data Analysis

• Visualization tools and libraries: Matplotlib, Seaborn
• Identifying patterns and trends in data

Machine Learning Algorithms

• Supervised learning: Regression (linear, logistic), classification (SVM, decision trees)
• Unsupervised learning: Clustering techniques (k-means, hierarchical)

⭐ Hands-on projects to practice: 

• Customer Segmentation Analysis: Analyze customer data to identify distinct segments for targeted marketing.
• Sentiment Analysis on Social Media: Build a sentiment analysis tool that analyzes social media posts to determine public sentiment.

Elective 6: DevOps

Version Control

• Introduction to Git: Repositories, commits, branches
• Collaboration with GitHub: Pull requests, issues, and project management

Containerization

• Introduction to Docker: Images, containers, Dockerfile
• Managing containers with Kubernetes: Pods, services, deployments

CI/CD

• Continuous Integration and Continuous Deployment: Concepts and tools (Jenkins, Travis CI)
• Automated testing and deployment strategies

Infrastructure as Code

• Introduction to Terraform and Ansible: Configuration management and provisioning

⭐ Hands-on projects to practice: 

•  CI/CD Pipeline for a Web Application: Set up a continuous integration and continuous deployment (CI/CD) pipeline for a web application.
• Infrastructure as Code with Terraform: Create and manage cloud infrastructure using Terraform.

Elective 7: Blockchain

Blockchain Fundamentals

• Definition and components of blockchain: Blocks, transactions, nodes
• Types of blockchain: Public, private, consortium

Consensus Algorithms

• Proof of Work vs. Proof of Stake: Mechanisms and Comparisons
• Other consensus mechanisms: Delegated Proof of Stake, Byzantine Fault Tolerance

Smart Contracts

• Definition and use cases of smart contracts
• Introduction to Ethereum and Solidity Programming

Blockchain Applications

• Cryptocurrencies: Bitcoin, Ethereum, and altcoins
• Use cases in supply chain, finance, and identity management

⭐ Hands-on projects to practice: 

• Simple Cryptocurrency: Develop a basic cryptocurrency using blockchain technology.
• Smart Contract for Voting System: Create a smart contract that allows users to vote in a secure and transparent manner.

Elective 8: Augmented Reality and Virtual Reality

AR/VR Fundamentals

• Definitions and differences between AR and VR
• Head-Mounted Displays (HMDs) and tracking technologies

AR Development

• Tools and frameworks: ARCore, ARKit, Unity
• Developing AR applications: Marker-based and markerless tracking

VR Development

• Tools and frameworks: OpenVR, Oculus SDK, Unity
• Developing immersive VR experiences: Interaction design and user experience

AR/VR Applications

• Use cases in gaming, education, training, and healthcare

⭐ Hands-on projects to practice: 

• AR Navigation App: Develop an augmented reality navigation application that helps users find directions in real-time.
• VR Educational Experience: Create a virtual reality application for educational purposes (e.g., a virtual museum tour).

Elective 9: Quantum Computing

Quantum Mechanics Basics

• Qubits, superposition, and entanglement
• Quantum gates and circuits

Quantum Algorithms

• Shor’s algorithm for factoring
• Grover’s algorithm for search optimization

Quantum Programming

• Introduction to quantum programming languages: Qiskit, Cirq
• Implementing quantum algorithms on quantum simulators and hardware

Quantum Applications

• Applications in cryptography, optimization, and simulation

⭐ Hands-on projects to practice: 

• Quantum Random Number Generator: Build a quantum random number generator using quantum principles.
• Quantum Algorithm Simulator: Develop a simulator for basic quantum algorithms (e.g., Grover’s algorithm).

Elective 10: Game Development

Game Engines

• Overview of popular game engines: Unity, Unreal Engine
• Setting up development environments

Game Programming

• Programming languages used in game development: C#, C++
• Game mechanics and physics: Collision detection, animations

Game Design

• Principles of game design: Mechanics, dynamics, aesthetics (MDA framework)
• Level design and user experience considerations

Game Platforms

• Developing games for PC, console, and mobile platforms
• Publishing and monetization strategies

⭐ Hands-on projects to practice: 

• 2D Platformer Game: Create a 2D platformer game where players navigate through levels.
• Multiplayer Online Game: Develop a multiplayer online game where players can interact in real-time.

Elective 11: Robotics

Robot Kinematics and Dynamics

• Forward and inverse kinematics
• Dynamics of robotic systems

Sensors and Actuators

• Types of sensors: Proximity, infrared, ultrasonic
• Types of actuators: Motors, servos, stepper motors

Robot Control

• Control systems: PID control, fuzzy logic control
• Implementing control algorithms in robotic systems

Robot Applications

• Industrial robots: Automation and manufacturing
• Service robots: Healthcare, hospitality, and domestic applications

⭐ Hands-on projects to practice: 

• Autonomous Robot Navigation: Build a robot that can navigate through an environment using sensors.
• Robotic Arm Control: Create a robotic arm that can perform tasks based on user input.

Elective 12: Natural Language Processing

Text Processing

• Techniques: Tokenization, stemming, lemmatization
• Text normalization and cleaning

Language Models

• N-grams and their applications
• Word embeddings: Word2Vec, GloVe

Text Classification

• Algorithms: Naive Bayes, Support Vector Machines (SVM), deep learning approaches
• Applications: Sentiment analysis, spam detection

NLP Applications

• Chatbots and virtual assistants
• Machine translation and information retrieval

⭐ Hands-on projects to practice: 

• Text Summarization Tool: Develop a tool that summarizes long articles or documents into concise summaries.
• Sentiment Analysis Application: Create an application that analyzes the sentiment of user-provided text.

Elective 13: Computer Vision

Image Processing

• Basics of image representation: Pixels, color spaces
• Common operations: Filtering, segmentation, edge detection

Object Detection

• Techniques: Haar cascades, YOLO, R-CNN
• Applications in surveillance and autonomous vehicles

Image Classification

• Convolutional Neural Networks (CNNs): Architecture and training
• Transfer learning and fine-tuning pre-trained models

Computer Vision Applications

• Face recognition and biometric systems
• Augmented reality and interactive applications

⭐ Hands-on projects to practice: 

• Object Detection System: Develop a system that detects and identifies objects in images or video streams.
• Facial Recognition Application: Create an application that recognizes and verifies faces in images or video.

BCA Course Curriculum Semester-Wise

The Bachelor of Computer Applications (BCA) program in India typically spans three years, divided into six semesters. It covers various technical subjects such as programming, data structures, database management, and networking.

The course fees usually range from ₹30,000 to ₹1,50,000 per year, depending on the institution.

Here’s the updated BCA course curriculum at a glance:

BCA course subjects and topics to learn

You need to stay updated on BCA subjects that are becoming increasingly essential in 2024. These are the important topics you must focus on:

Data science and analysis

Data science is one of the most in-demand skills in 2024 as per NASSCOM. A data analytics role also has a higher transition propensity. 

Consider these following skills and tools as per ODSC under this subject:

The data science frameworks and tools which are a must-haves:

AI and Machine Learning 

The same report found that in 2024, India ranks first globally in AI and ML skills. However, there’s still a 51% gap between the demand for these skills and the supply. You can take advantage of this opportunity and position yourself ahead by learning these concepts below:

According to Coursera, these are the most important concepts in machine learning:

• Statistical analysis and mathematical data manipulation 
• Algorithm development 
• Neural network architectures 
• Deploying deep learning models 

A PwC report released in 2024 on AI and its effect on workforce revealed the most required skills:

• Prompt engineering 
• Data analysis 

Cybersecurity 

A rise in technology also means an increase in cyber threats. That’s why having an understanding of topics like data protection, risk management, network security, and ethical hacking can be really valuable for you as a student.

One way to get started is to explore these best certifications on Coursera from IBM, Google, Microsoft, Infosec, and so on. 

Cloud computing 

Now, with the meteoric adoption of AI and new tech, nearly 65% of top-performing companies are increasing their cloud budgets. Since most businesses are shifting to cloud-based software, now’s the perfect time for you to learn how to deploy and manage cloud applications.

A few focus areas:

• Cloud architecture 
• Containerization 
• Serverless computing, and 
• DevOps practices

Mobile and web application development 

With businesses moving their business, entertainment, and even education online, the demand for responsive, friendly apps will continue to increase. Hence, there’s always a need for developers who can build and scale mobile and web applications. 

In fact, according to Simplilearn, a career in mobile applications was ranked 2nd in highest paying jobs. The average salary an Indian earns is above ₹6 LPA.

Technologies to learn mobile and web development:

• Front-end (HTML/CSS, JavaScript, React.js, Angular, and Vue.js)
• Back-end (Django, Node.js, Ruby on Rails, and Express.js)
• Mobile development (Flutter, React Native, Swift, Kotlin)
• Database (MySQL/PostgreSQL, MongoDB)
• Version control (Git)

BCA course fees and duration 2024

Pursuing a BCA program will equip you with important topics and skills mentioned above. However, the cost can change depending on its duration. Let’s explore what might be the best fit for you!

What is the course fee of BCA courses? 

The course fee of BCA courses range from ₹10,000 to ₹5,00,000. For government courses, the fee is typically lower, ranging between ₹30,000 to ₹50,000. If you want to choose between private or government institutions, consider:

• Faculty quality 
• Infrastructure 
• Placement opportunities 
• Accreditation 

While government colleges provide better facilities, private ones may provide better industry exposure and advanced facilities. Make sure to balance your decision based on both budget and educational requirements. 

BCA Course Duration 

The Bachelor of Computer Application (BCA) lasts for three years, divided into six semesters. However, NEP has also introduced non-mandatory 4-year undergraduate programs, including BCA. 

It’s ideal for those who want to opt for international jobs, higher studies, internships, research, and practical learning. Students can exit after 3 years with a standard BCA degree or complete the 4th year to earn a BCA Honors/Research degree.

Be it a 3-year or 4-year program, it prepares you thoroughly for a career in IT companies or higher education!

Who is eligible for BCA courses?

To enroll in the Bachelor of Computer Applications (BCA) program in India, candidates must meet the following requirements:

• Educational Qualification: Completion of higher secondary education (10+2) from a recognized board, preferably with a focus on science or mathematics.
• Minimum Marks: Some institutions may require a minimum percentage in the qualifying examination (typically around 50%).
• Entrance Exams: Certain colleges may conduct entrance exams for admission.

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).