Comprehensive Course Structure
The Computer Science program at Shri Krishna University Chhatarpur is structured over eight semesters, with a carefully balanced mix of core courses, departmental electives, science electives, and laboratory sessions. This structure ensures that students develop a strong foundation in computer science principles while also gaining exposure to specialized areas of interest.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Computer Science | 3-0-0-3 | - |
| 1 | CS102 | Programming in C | 2-0-2-3 | - |
| 1 | CS103 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | CS104 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | CS105 | Communication Skills | 2-0-0-2 | - |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS102 |
| 2 | CS202 | Object-Oriented Programming | 2-0-2-3 | CS102 |
| 2 | CS203 | Computer Organization and Architecture | 3-0-0-3 | CS104 |
| 2 | CS204 | Discrete Mathematics | 3-0-0-3 | CS103 |
| 2 | CS205 | Database Management Systems | 3-0-0-3 | CS201 |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS201 |
| 3 | CS302 | Software Engineering | 3-0-0-3 | CS202 |
| 3 | CS303 | Computer Networks | 3-0-0-3 | CS201 |
| 3 | CS304 | Design and Analysis of Algorithms | 3-0-0-3 | CS201 |
| 3 | CS305 | Computer Graphics | 3-0-0-3 | CS202 |
| 4 | CS401 | Artificial Intelligence | 3-0-0-3 | CS301 |
| 4 | CS402 | Machine Learning | 3-0-0-3 | CS301 |
| 4 | CS403 | Cybersecurity | 3-0-0-3 | CS301 |
| 4 | CS404 | Web Development | 3-0-0-3 | CS202 |
| 4 | CS405 | Mobile Application Development | 3-0-0-3 | CS202 |
| 5 | CS501 | Advanced Data Structures | 3-0-0-3 | CS301 |
| 5 | CS502 | Database Systems | 3-0-0-3 | CS205 |
| 5 | CS503 | Cloud Computing | 3-0-0-3 | CS301 |
| 5 | CS504 | Human-Computer Interaction | 3-0-0-3 | CS202 |
| 5 | CS505 | Big Data Analytics | 3-0-0-3 | CS301 |
| 6 | CS601 | Research Methodology | 3-0-0-3 | CS501 |
| 6 | CS602 | Project Management | 3-0-0-3 | CS302 |
| 6 | CS603 | Special Topics in Computer Science | 3-0-0-3 | CS501 |
| 6 | CS604 | Internship | 0-0-0-6 | CS501 |
| 7 | CS701 | Capstone Project | 0-0-0-12 | CS601 |
| 7 | CS702 | Thesis | 0-0-0-12 | CS701 |
| 8 | CS801 | Advanced Research | 0-0-0-12 | CS702 |
Advanced Departmental Electives
Artificial Intelligence and Machine Learning
This course introduces students to the fundamental concepts and techniques of artificial intelligence and machine learning. It covers topics such as search algorithms, knowledge representation, planning, and learning from data. Students will also explore advanced topics such as neural networks, deep learning, and reinforcement learning. The course emphasizes both theoretical understanding and practical implementation through hands-on projects.
Advanced Cybersecurity
This elective course provides an in-depth exploration of modern cybersecurity challenges and solutions. Students will learn about network security, cryptography, ethical hacking, and risk management. The course includes practical labs where students will simulate real-world security scenarios and develop defensive strategies. This course is designed to prepare students for careers in cybersecurity consulting and defense.
Cloud Computing and Distributed Systems
This course focuses on the design and implementation of scalable, distributed systems. Students will study cloud platforms, virtualization, containerization, and microservices. The course emphasizes practical skills and real-world applications, with students working on projects involving cloud deployment and management. Students will also learn about DevOps practices and performance optimization in distributed environments.
Internet of Things and Embedded Systems
This elective explores the development of systems that are embedded in physical devices and connected to the internet. Students will learn about microcontrollers, sensors, real-time systems, and network protocols. The course includes hands-on projects involving robotics, smart home systems, and industrial automation. Students will gain experience in both hardware and software development for IoT applications.
Data Science and Analytics
This course provides students with the tools and techniques for extracting insights from large datasets. Students will learn about statistical analysis, data mining, visualization, and predictive modeling. The course emphasizes practical skills and real-world applications, with students working on projects involving big data technologies such as Hadoop and Spark. Students will also gain experience in using industry-standard tools such as Python, R, and SQL.
Software Engineering and Project Management
This course focuses on the principles and practices of software engineering and project management. Students will learn about software architecture, agile development, testing, and project planning. The course emphasizes practical skills and real-world applications, with students working on full-stack development projects and contributing to open-source initiatives. Students will also gain experience in using project management tools and methodologies.
Game Development and Multimedia
This elective is designed for students interested in the creation of interactive media and entertainment. The course covers game design, 3D modeling, animation, and multimedia programming. Students will gain experience with game engines such as Unity and Unreal, and work on projects that simulate real-world game development environments. The course also explores the business aspects of game development and monetization strategies.
Blockchain and Cryptocurrency
This emerging course focuses on the technology behind blockchain and its applications in finance, supply chain, and digital identity. Students will learn about distributed ledger technology, smart contracts, and cryptocurrency systems. The course includes hands-on projects involving blockchain development and decentralized applications. Students will also explore the regulatory and ethical considerations of blockchain technology.
Mobile Application Development
This course prepares students for careers in mobile software development. The curriculum covers mobile platforms such as Android and iOS, mobile UI/UX design, and cross-platform development. Students will also learn about mobile security, app store optimization, and user engagement strategies. The course emphasizes practical skills and real-world applications, with students working on projects that simulate real-world mobile development environments.
Human-Computer Interaction and User Experience
This course focuses on the design and evaluation of user interfaces and experiences. Students will learn about user research, interaction design, usability testing, and prototyping. The curriculum includes courses in psychology, design thinking, and accessibility, preparing students for roles in UX design and human factors engineering. Students will also gain experience in using design tools and conducting user studies.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that students learn best when they are actively engaged in solving real-world problems. This approach emphasizes hands-on experience, collaboration, and innovation, preparing students for careers in a rapidly evolving field.
Mini-Projects
Mini-projects are an integral part of the curriculum, typically undertaken in the second and third years. These projects are designed to reinforce theoretical concepts through practical application. Students work in small teams to develop solutions to specific problems, often in collaboration with industry partners. The projects are evaluated based on technical merit, innovation, and presentation skills.
Final-Year Thesis/Capstone Project
The final-year thesis or capstone project is a comprehensive endeavor that allows students to apply their knowledge to a significant problem or challenge. Students work closely with faculty mentors to develop a research or development project that addresses a real-world need. The project is typically completed over a semester and involves extensive research, design, implementation, and evaluation phases.
Project Selection and Mentorship
Students select their projects based on their interests and career goals, with guidance from faculty mentors. The department maintains a database of project ideas, and students can also propose their own projects. Faculty mentors are assigned based on their expertise and the relevance of their research to the student's project. Regular meetings and feedback sessions ensure that students stay on track and receive support throughout their project journey.