BSc–MSc Computer Science Syllabus Structure (5 Years)
The integrated BSc–MSc Computer Science syllabus is designed to provide a smooth transition from undergraduate fundamentals to postgraduate-level specialization and research.
The curriculum focuses on programming, systems, data, intelligence, and research methodology.
Year 1: Foundation in Computing & Mathematics
The first year builds a strong base in programming, mathematics, and computer fundamentals.
Semester 1
- Programming in C: Variables, loops, functions, and arrays.
- Discrete Mathematics: Logic, sets, relations, and functions.
- Computer Fundamentals: Hardware, software, and operating basics.
- Communication Skills: Technical writing and presentations.
Semester 2
- Object-Oriented Programming (C++/Java): Classes, objects, inheritance.
- Mathematics for Computing: Linear algebra and probability.
- Digital Logic: Number systems, logic gates, and circuits.
- Environmental Studies: Sustainability and ethics.
Year 2: Core Computing Subjects
The second year focuses on essential computer science subjects required for software development and system understanding.
Semester 3
- Data Structures: Arrays, stacks, queues, linked lists, trees.
- Database Management Systems: SQL, normalization, transactions.
- Computer Organization: CPU, memory, and instruction cycles.
- Python Programming: Scripting and problem-solving.
Semester 4
- Operating Systems: Processes, memory management, file systems.
- Computer Networks: OSI model, TCP/IP, routing.
- Software Engineering: SDLC, testing, and project management.
- Web Technologies: HTML, CSS, JavaScript basics.
Year 3: Advanced Computer Science Concepts
The third year introduces advanced algorithms, theory, and application-oriented subjects.
Semester 5
- Design & Analysis of Algorithms: Sorting, searching, complexity.
- Artificial Intelligence: Search techniques and knowledge representation.
- Computer Graphics: Rendering, transformations, and visualization.
- Elective I: Mobile Computing / IoT Basics.
Semester 6
- Machine Learning: Supervised and unsupervised learning.
- Compiler Design: Lexical analysis, parsing, code generation.
- Data Warehousing & Mining: Data analysis techniques.
- Mini Project: Application-based project.
Year 4: Postgraduate-Level Specialization
The fourth year marks the transition to MSc-level coursework with deeper specialization.
Semester 7
- Advanced Database Systems: NoSQL, distributed databases.
- Cloud Computing: Virtualization, cloud models, services.
- Cyber Security: Cryptography and network security.
- Elective II: Big Data Analytics / DevOps.
Semester 8
- Deep Learning: Neural networks and applications.
- Research Methodology: Literature review and research design.
- Advanced Elective: AI Ethics / Blockchain.
- Industry Internship: Practical exposure.
Year 5: Research, Dissertation & Professional Readiness
The final year focuses on independent research, advanced electives, and dissertation work.
Semester 9
- Advanced Topics in Computer Science: Emerging technologies.
- Elective III: Specialized domain subject.
- Seminar: Research paper presentation.
Semester 10
- Dissertation / Thesis: Original research project.
- Viva Voce: Defense of research work.
Recommended Books for BSc–MSc Computer Science
| Subject |
Book Title |
Author |
| Programming |
The C Programming Language |
Kernighan & Ritchie |
| Data Structures |
Data Structures Using C |
Reema Thareja |
| Algorithms |
Introduction to Algorithms |
Cormen et al. |
| AI & ML |
Artificial Intelligence: A Modern Approach |
Stuart Russell |
BSc–MSc Computer Science Syllabus FAQs
Q1: Does the integrated syllabus cover both undergraduate and postgraduate computer science topics?
Yes, the syllabus starts with basic concepts.
It gradually moves to MSc-level subjects.
Academic progression is well structured.
Q2: Is programming taught from the beginner level in the first year?
Yes, programming begins from basics.
Multiple languages are introduced.
Logical thinking is emphasized.
Q3: Are advanced technologies like AI and Machine Learning part of the syllabus?
Yes, AI and ML are core subjects.
Practical applications are covered.
Advanced topics appear in later years.
Q4: Does the syllabus include internships and project work?
Yes, internships are included.
Projects are mandatory each year.
Industry exposure is ensured.
Q5: Is research methodology taught before the final dissertation?
Yes, research methodology is included.
It prepares students for thesis work.
Academic writing is taught.
Q6: Are elective subjects available in the integrated computer science syllabus?
Yes, electives are offered from mid-program.
Students can specialize in areas of interest.
Electives enhance career focus.
Q7: Can the syllabus change based on industry trends and university updates?
Yes, syllabus revisions are common.
Universities update courses regularly.
Changes keep the program relevant.
Q8: Is the syllabus suitable for students aiming for research or PhD programs?
Yes, the syllabus is research-oriented.
Dissertation work supports PhD preparation.
Academic depth is strong.
