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Fees
₹5,00,000
Placement
94.5%
Avg Package
₹7,50,000
Highest Package
₹12,00,000
Fees
₹5,00,000
Placement
94.5%
Avg Package
₹7,50,000
Highest Package
₹12,00,000
Seats
200
Students
2,000
Seats
200
Students
2,000
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Computer Science | 3-0-0-3 | - |
| 1 | CS102 | Mathematics for Computer Science I | 4-0-0-4 | - |
| 1 | CS103 | Basic Programming Using C | 2-0-2-4 | - |
| 1 | CS104 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | CS105 | Chemistry for Computer Science | 3-0-0-3 | - |
| 1 | CS106 | English Communication Skills | 2-0-0-2 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS103 |
| 2 | CS202 | Mathematics for Computer Science II | 4-0-0-4 | CS102 |
| 2 | CS203 | Object-Oriented Programming Using Java | 2-0-2-4 | CS103 |
| 2 | CS204 | Database Management Systems | 3-0-0-3 | CS201 |
| 2 | CS205 | Computer Organization and Architecture | 3-0-0-3 | - |
| 2 | CS206 | Physics Lab | 0-0-2-1 | CS104 |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS205 |
| 3 | CS302 | Software Engineering Principles | 3-0-0-3 | CS201 |
| 3 | CS303 | Web Technologies and Development | 2-0-2-4 | CS203 |
| 3 | CS304 | Computer Networks | 3-0-0-3 | CS205 |
| 3 | CS305 | Mathematics for Computer Science III | 4-0-0-4 | CS202 |
| 3 | CS306 | Discrete Mathematics | 3-0-0-3 | CS202 |
| 4 | CS401 | Compiler Design | 3-0-0-3 | CS301 |
| 4 | CS402 | Artificial Intelligence and Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS403 | Cybersecurity Fundamentals | 3-0-0-3 | CS304 |
| 4 | CS404 | Distributed Systems | 3-0-0-3 | CS301 |
| 4 | CS405 | Data Science and Analytics | 3-0-0-3 | CS201 |
| 4 | CS406 | Human-Computer Interaction | 3-0-0-3 | CS303 |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS201 |
| 5 | CS502 | Mobile Application Development | 3-0-0-3 | CS303 |
| 5 | CS503 | Internet of Things (IoT) | 3-0-0-3 | CS304 |
| 5 | CS504 | Cloud Computing | 3-0-0-3 | CS301 |
| 5 | CS505 | Software Testing and Quality Assurance | 3-0-0-3 | CS302 |
| 5 | CS506 | Research Methodology | 2-0-0-2 | - |
| 6 | CS601 | Specialized Elective I | 3-0-0-3 | - |
| 6 | CS602 | Specialized Elective II | 3-0-0-3 | - |
| 6 | CS603 | Specialized Elective III | 3-0-0-3 | - |
| 6 | CS604 | Specialized Elective IV | 3-0-0-3 | - |
| 6 | CS605 | Mini Project I | 2-0-0-2 | - |
| 6 | CS606 | Mini Project II | 2-0-0-2 | - |
| 7 | CS701 | Capstone Project - Phase I | 3-0-0-3 | - |
| 7 | CS702 | Capstone Project - Phase II | 4-0-0-4 | CS701 |
| 7 | CS703 | Internship | 2-0-0-2 | - |
| 8 | CS801 | Final Year Thesis | 4-0-0-4 | CS702 |
| 8 | CS802 | Elective Course - Advanced Topics | 3-0-0-3 | - |
| 8 | CS803 | Professional Ethics and Social Responsibility | 2-0-0-2 | - |
| 8 | CS804 | Entrepreneurship in Tech | 2-0-0-2 | - |
| 8 | CS805 | Final Project Presentation | 2-0-0-2 | CS801 |
Each course in the Bachelor of Computer Science program at Gyan Ganga Institute of Technology and Sciences is designed to build upon foundational knowledge while introducing students to specialized domains. The curriculum ensures a balance between theoretical understanding and practical application, preparing students for both industry roles and further academic pursuits.
The department offers several advanced elective courses that allow students to specialize in areas of interest. These courses are designed to provide depth and innovation in cutting-edge fields of computer science.
Artificial Intelligence and Machine Learning: This course delves into the principles and applications of machine learning, including supervised and unsupervised learning techniques. Students learn about neural networks, deep learning architectures, and reinforcement learning algorithms. Practical sessions involve building models using frameworks like TensorFlow and PyTorch.
Cybersecurity Fundamentals: This course covers essential concepts in cybersecurity, including network security, cryptography, ethical hacking, and risk management. Students engage in hands-on labs to simulate real-world attack scenarios and develop defensive strategies.
Cloud Computing: Focused on cloud architecture and services, this course introduces students to platforms like AWS, Azure, and GCP. Topics include virtualization, containerization, microservices, and scalable application deployment.
Data Science and Analytics: This course explores statistical methods, data mining, and visualization tools used in modern analytics pipelines. Students work with big data technologies like Hadoop and Spark to extract insights from complex datasets.
Distributed Systems: Students learn about the design and implementation of distributed systems, including concepts like consensus algorithms, fault tolerance, and scalability. The course includes projects involving real-time system simulations.
Human-Computer Interaction: This course examines how people interact with computing devices and how interfaces can be designed for usability and accessibility. It combines theory with practical prototyping and user testing exercises.
Mobile Application Development: This elective provides comprehensive training in developing applications for iOS and Android platforms. Students learn native and cross-platform development frameworks, mobile UI design principles, and app deployment strategies.
Internet of Things (IoT): The course focuses on integrating physical devices with digital networks, covering sensor technologies, embedded systems programming, and smart city applications.
Software Testing and Quality Assurance: This course teaches various testing methodologies, including unit testing, integration testing, performance testing, and automated testing tools. It emphasizes quality assurance processes in software development life cycles.
Advanced Algorithms: This course covers advanced algorithmic techniques such as dynamic programming, graph algorithms, and approximation algorithms. Students solve complex computational problems using mathematical modeling and analysis.
The Bachelor of Computer Science program at Gyan Ganga Institute of Technology and Sciences places a strong emphasis on project-based learning to enhance practical skills and foster innovation among students. This approach aligns with industry demands for hands-on experience and problem-solving capabilities.
Mini-projects begin in the third year, where students work in teams to address real-world challenges using programming languages, databases, and software engineering practices. These projects are supervised by faculty mentors who guide students through design, implementation, and evaluation phases.
The final-year capstone project is a significant undertaking that integrates all learned concepts into a substantial solution. Students select projects based on their interests or industry needs, often collaborating with external organizations or research labs. The process includes proposal writing, milestone reviews, and a final presentation to an expert panel.
Evaluation criteria for these projects consider technical proficiency, creativity, documentation quality, teamwork, and project management skills. Faculty mentors play a crucial role in guiding students throughout the project lifecycle, ensuring alignment with academic standards and industry best practices.
