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Meri Shiksha

Bachelor of Science+Master of Science in Computer Science Syllabus

Computer Eligibility: 10+2 Duration: 5 Yearly Course Mode: Regular

Bachelor of Science+Master of Science in Computer Science Syllabus

Table of Contents

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.