Curriculum Overview
The Computer Science program at Gyanveer University Sagar is structured over eight semesters, ensuring a comprehensive and progressive educational experience. Each semester builds upon previous knowledge while introducing new concepts relevant to the evolving landscape of computing technology.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CSE101 | Introduction to Programming | 3-0-2-4 | - |
| 1 | CSE102 | Mathematics I | 3-0-0-3 | - |
| 1 | CSE103 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | CSE104 | Chemistry for Computer Science | 3-0-0-3 | - |
| 1 | CSE105 | English Communication Skills | 2-0-0-2 | - |
| 1 | CSE106 | Introduction to Computer Science | 3-0-0-3 | - |
| 1 | CSE107 | Programming Laboratory | 0-0-4-2 | - |
| 2 | CSE201 | Data Structures and Algorithms | 3-0-2-4 | CSE101 |
| 2 | CSE202 | Mathematics II | 3-0-0-3 | CSE102 |
| 2 | CSE203 | Object-Oriented Programming | 3-0-2-4 | CSE101 |
| 2 | CSE204 | Computer Organization and Architecture | 3-0-0-3 | - |
| 2 | CSE205 | Discrete Mathematics | 3-0-0-3 | - |
| 2 | CSE206 | Operating Systems | 3-0-2-4 | CSE201 |
| 2 | CSE207 | Data Structures and Algorithms Laboratory | 0-0-4-2 | CSE101 |
| 3 | CSE301 | Database Management Systems | 3-0-2-4 | CSE201 |
| 3 | CSE302 | Software Engineering | 3-0-2-4 | CSE201 |
| 3 | CSE303 | Computer Networks | 3-0-2-4 | CSE201 |
| 3 | CSE304 | Design and Analysis of Algorithms | 3-0-0-3 | CSE201 |
| 3 | CSE305 | Probability and Statistics | 3-0-0-3 | CSE102 |
| 3 | CSE306 | Mathematics III | 3-0-0-3 | CSE102 |
| 3 | CSE307 | Database Management Systems Laboratory | 0-0-4-2 | CSE201 |
| 4 | CSE401 | Artificial Intelligence and Machine Learning | 3-0-2-4 | CSE201 |
| 4 | CSE402 | Cybersecurity Fundamentals | 3-0-2-4 | CSE201 |
| 4 | CSE403 | Data Science and Analytics | 3-0-2-4 | CSE201 |
| 4 | CSE404 | Web Technologies | 3-0-2-4 | CSE201 |
| 4 | CSE405 | Mobile Application Development | 3-0-2-4 | CSE201 |
| 4 | CSE406 | Embedded Systems and IoT | 3-0-2-4 | CSE201 |
| 4 | CSE407 | Project Work - I | 0-0-6-6 | - |
| 5 | CSE501 | Advanced Machine Learning | 3-0-2-4 | CSE401 |
| 5 | CSE502 | Network Security | 3-0-2-4 | CSE402 |
| 5 | CSE503 | Big Data Analytics | 3-0-2-4 | CSE403 |
| 5 | CSE504 | Cloud Computing | 3-0-2-4 | CSE301 |
| 5 | CSE505 | Human-Computer Interaction | 3-0-2-4 | - |
| 5 | CSE506 | Software Testing and Quality Assurance | 3-0-2-4 | CSE302 |
| 5 | CSE507 | Project Work - II | 0-0-6-6 | - |
| 6 | CSE601 | Computer Vision and Image Processing | 3-0-2-4 | CSE401 |
| 6 | CSE602 | Blockchain Technologies | 3-0-2-4 | - |
| 6 | CSE603 | Reinforcement Learning | 3-0-2-4 | CSE501 |
| 6 | CSE604 | Game Development | 3-0-2-4 | - |
| 6 | CSE605 | Distributed Systems | 3-0-2-4 | CSE303 |
| 6 | CSE606 | Advanced Web Development | 3-0-2-4 | CSE404 |
| 6 | CSE607 | Project Work - III | 0-0-6-6 | - |
| 7 | CSE701 | Capstone Project I | 0-0-8-8 | - |
| 7 | CSE702 | Research Methodology | 3-0-0-3 | - |
| 7 | CSE703 | Special Topics in Computer Science | 3-0-0-3 | - |
| 7 | CSE704 | Industrial Training | 0-0-6-6 | - |
| 7 | CSE705 | Entrepreneurship and Innovation | 2-0-0-2 | - |
| 8 | CSE801 | Capstone Project II | 0-0-8-8 | - |
| 8 | CSE802 | Thesis Writing and Presentation | 2-0-0-2 | - |
| 8 | CSE803 | Internship Report | 0-0-6-6 | - |
| 8 | CSE804 | Final Year Project | 0-0-12-12 | - |
Detailed Course Descriptions
Advanced Machine Learning is a course designed to provide students with an in-depth understanding of modern machine learning techniques and algorithms. It covers supervised, unsupervised, and reinforcement learning methods, including neural networks, decision trees, support vector machines, clustering algorithms, and policy gradient methods.
Cybersecurity Fundamentals introduces students to the principles of information security, including network security, cryptography, access control, risk management, and incident response. The course includes hands-on labs where students simulate attacks and defend against them using industry-standard tools like Wireshark, Metasploit, and Kali Linux.
Data Science and Analytics teaches students how to extract insights from large datasets using statistical methods, data visualization, and machine learning techniques. Students learn to use Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn to perform exploratory data analysis and build predictive models.
Web Technologies covers the development of dynamic web applications using modern technologies like HTML5, CSS3, JavaScript, Node.js, Express.js, React, Angular, and MongoDB. Students learn full-stack development concepts and gain experience building responsive websites and APIs for real-world applications.
Mobile Application Development focuses on creating cross-platform mobile apps using frameworks like Flutter and React Native. The course emphasizes user interface design, app architecture, integration with backend services, and deployment to major app stores.
Embedded Systems and IoT explores the design and implementation of embedded systems that interact with physical environments through sensors and actuators. Students learn about microcontroller programming, real-time operating systems, wireless communication protocols, and device integration in IoT ecosystems.
Computer Vision and Image Processing delves into the techniques used to analyze and interpret visual data from digital images or videos. Topics include image filtering, edge detection, feature extraction, object recognition, facial recognition, and deep learning-based computer vision models.
Blockchain Technologies examines the architecture and applications of blockchain systems, including distributed consensus mechanisms, smart contracts, cryptocurrency systems, and decentralized finance (DeFi) platforms. Students learn to develop and deploy blockchain solutions using Ethereum and Hyperledger frameworks.
Reinforcement Learning introduces students to algorithms that enable agents to learn optimal behavior through trial and error in environments with rewards or penalties. The course covers Markov decision processes, Q-learning, policy gradients, actor-critic methods, and applications in robotics and game playing.
Game Development provides a comprehensive overview of the game development pipeline, including design principles, 3D modeling, animation, scripting, sound integration, and platform-specific optimization. Students work on collaborative projects to create interactive games using engines like Unity or Unreal Engine.
Distributed Systems explores the challenges and solutions involved in building systems that span multiple computers connected via networks. Topics include fault tolerance, consistency models, distributed algorithms, cloud computing architectures, and microservices design patterns.
Advanced Web Development focuses on modern web frameworks and technologies for scalable application development. Students learn to build RESTful APIs, implement authentication and authorization mechanisms, integrate third-party services, and optimize performance using caching strategies and load balancing techniques.
Project-Based Learning Philosophy
At Gyanveer University Sagar, we believe that project-based learning is essential for developing practical skills and preparing students for real-world challenges. Our approach emphasizes iterative development cycles, collaborative teamwork, and mentorship from faculty members with industry experience.
Mini-projects are integrated throughout the program to reinforce theoretical concepts learned in lectures. These projects typically span one semester and involve working on small-scale software or research tasks under the guidance of a faculty advisor. Students learn essential project management skills, including requirement analysis, design documentation, version control, testing strategies, and presentation techniques.
The final-year thesis or capstone project is a culmination of all learning experiences. Students select a topic aligned with their interests and career goals, often collaborating with industry partners on actual problems they face in practice. The project involves extensive research, prototyping, experimentation, documentation, and public defense before a panel of faculty members.
Faculty mentors are assigned based on the student's area of interest and the availability of resources within the department. Regular meetings, progress reviews, and milestone tracking ensure that students stay on track toward completing their projects successfully.