*Year 1: Foundations*

*Semester 1* 

1. *Introduction to Programming* 

   - Basics of programming (variables, loops, conditionals). 

   - Language: Python/Java/C. 

   - Problem-solving and algorithm design. 

2. *Discrete Mathematics* 

   - Logic, sets, relations, functions, combinatorics. 

   - Graph theory basics. 

3. *Computer Fundamentals* 

   - History of computing, hardware/software basics, OS fundamentals. 

4. *Calculus I* 

   - Limits, derivatives, integrals. 

5. *Communication Skills* 

   - Technical writing and presentations. 

 

*Semester 2* 

1. *Object-Oriented Programming (OOP)* 

   - Classes, inheritance, polymorphism (using Java/C++). 

2. *Data Structures* 

   - Arrays, linked lists, stacks, queues, trees. 

3. *Digital Logic Design* 

   - Boolean algebra, combinational/sequential circuits. 

4. *Calculus II* 

   - Multivariable calculus, series. 

5. *Physics for Computer Science* 

   - Basics of electricity, magnetism, and circuits. 

 

 *Year 2: Core Concepts* 

*Semester 3* 

1. *Algorithms* 

   - Sorting, searching, dynamic programming, complexity analysis. 

2. *Computer Organization & Architecture* 

   - CPU design, memory hierarchy, assembly language. 

3. *Probability & Statistics* 

   - Distributions, hypothesis testing, data analysis. 

4. *Database Systems* 

   - SQL, relational models, normalization. 

5. *Operating Systems* 

   - Processes, threads, memory management, file systems. 

 

*Semester 4* 

1. *Software Engineering* 

   - SDLC, Agile, UML, testing, project management. 

2. *Theory of Computation* 

   - Automata, formal languages, Turing machines. 

3. *Linear Algebra* 

   - Matrices, vectors, eigenvalues. 

4. *Web Development* 

   - HTML/CSS, JavaScript, frontend/backend basics. 

5. *Networking Fundamentals* 

   - OSI model, TCP/IP, routing, network security basics. 

 

*Year 3: Advanced Topics* 

*Semester 5* 

1. *Artificial Intelligence (AI)* 

   - Search algorithms, machine learning basics, neural networks. 

2. *Compiler Design* 

   - Lexical analysis, parsing, code generation. 

3. *Computer Graphics* 

   - Rendering, OpenGL, 3D transformations. 

4. *Elective I* (e.g., Cybersecurity, Cloud Computing, IoT). 

5. *Lab/Practical* 

   - Mini-projects (e.g., app development, database design). 

 

*Semester 6* 

1. *Machine Learning* 

   - Supervised/unsupervised learning, regression, classification. 

2. *Distributed Systems* 

   - Concurrency, consistency, distributed algorithms. 

3. *Human-Computer Interaction (HCI)* 

   - UI/UX design principles. 

4. *Elective II* (e.g., Data Science, Blockchain, Game Dev). 

5. *Internship/Industry Project* 

 

*Year 4: Specialization & Capstone* 

*Semester 7* 

1. *Advanced Electives* 

   - Topics like Big Data, Robotics, NLP, or Quantum Computing. 

2. *Ethics in Computing* 

   - Privacy, cybersecurity laws, AI ethics. 

3. *Research Methodology* 

   - Preparing for thesis/capstone projects. 

4. *Open-Source Contribution* 

   - Collaborative coding projects. 

 

*Semester 8* 

1. *Capstone Project* 

   - End-to-end software/hardware project (team-based). 

2. *Elective III* (e.g., Advanced Algorithms, Bioinformatics). 

3. *Professional Development* 

   - Resume building, interview prep, career guidance. 

 

*Elective Options* 

- *Cybersecurity* 

- *Cloud Computing (AWS/Azure) * 

- *Mobile App Development* 

- *Data Science & Analytics* 

- *Game Development* 

- *Internet of Things (IoT)* 

- *Quantum Computing* 

 

*Additional Requirements* 

- *Mathematics: * Discrete Math, Linear Algebra, Calculus, Statistics. 

- *Labs: * Programming labs, hardware labs, and simulations. 

- *Internships/Co-op: * Industry experience (often optional but recommended).