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B-TECH-M-TECH in Computer Science And Engineering at Indian Institute of Technology Kanpur
Kanpur Nagar, Uttar Pradesh
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About the Specialization
What is Computer Science and Engineering at Indian Institute of Technology Kanpur Kanpur Nagar?
This B.Tech - M.Tech Computer Science and Engineering program at IIT Kanpur focuses on an in-depth understanding of computing principles, combining foundational knowledge with advanced research. It offers a unique dual degree path, addressing the increasing demand for highly skilled professionals and researchers in India''''s rapidly expanding technology sector. The program emphasizes both theoretical rigor and practical application, preparing students for leadership roles.
Who Should Apply?
This program is ideal for high-achieving fresh graduates from 10+2 who have excelled in JEE Advanced and possess a strong aptitude for mathematics, logical reasoning, and problem-solving. It also caters to those aspiring for a research-oriented career or leadership positions in the Indian tech industry, seeking a comprehensive education beyond a traditional bachelor''''s degree. Students with a keen interest in cutting-edge areas like AI, ML, Data Science, and Systems will thrive here.
Why Choose This Course?
Graduates of this program can expect to secure top positions in leading Indian and multinational technology companies operating in India, including roles in software development, data science, AI/ML engineering, and cybersecurity. Entry-level salaries typically range from INR 15-30 LPA, with significant growth potential. The dual degree also provides a strong foundation for pursuing doctoral studies or entrepreneurial ventures within India''''s thriving startup ecosystem.
Student Success Practices
Foundation Stage
Master Core Programming & Math- (Semester 1-2)
Consistently practice programming fundamentals (C/Python) and strengthen mathematical concepts (Calculus, Linear Algebra). Solve problems on platforms regularly.
Tools & Resources
HackerRank, CodeChef, LeetCode (easy level), Khan Academy, NPTEL videos for MTH/PHY
Career Connection
Essential for all technical roles; forms the bedrock for advanced CS subjects and coding interviews.
Engage in Departmental Clubs & Societies- (Semester 1-2)
Actively participate in clubs like Programming Club, Robotics Club, or technical societies to apply theoretical knowledge and build practical skills.
Tools & Resources
Official club websites, departmental notice boards, senior mentors
Career Connection
Develops teamwork, leadership, and project experience, which are highly valued by recruiters.
Build Strong Peer Networks- (Semester 1-2)
Form study groups and collaborate with peers on assignments and projects. Leverage collective knowledge and learn from diverse perspectives.
Tools & Resources
Campus study areas, online collaboration tools like Discord/Slack, library resources
Career Connection
Fosters communication and collaboration skills, crucial for working in teams in the professional world.
Intermediate Stage
Deep Dive into Data Structures & Algorithms (DSA)- (Semester 3-5)
Beyond course requirements, dedicate significant time to advanced DSA problems and competitive programming. Understand complexity analysis thoroughly.
Tools & Resources
GeeksforGeeks, InterviewBit, TopCoder, Codeforces, relevant textbooks
Career Connection
Critical for cracking technical interviews at product-based companies and optimizing software performance.
Pursue Practical Projects & Open Source Contributions- (Semester 4-5)
Work on self-initiated projects, participate in hackathons, or contribute to open-source projects. Focus on applying learned concepts in real-world scenarios.
Tools & Resources
GitHub, Kaggle, hackathon platforms (Devfolio), local community meetups
Career Connection
Builds a strong portfolio, demonstrates practical skills, and provides exposure to industry best practices.
Explore Specialization Electives & Research Areas- (Semester 5)
Attend departmental seminars, interact with professors about their research, and select electives that align with emerging fields like AI/ML, Cybersecurity, or Systems.
Tools & Resources
Departmental research labs, faculty websites, NPTEL advanced courses
Career Connection
Helps in identifying career interests, preparing for advanced studies (M.Tech/Ph.D.), and gaining specialized knowledge for niche roles.
Advanced Stage
Secure High-Impact Internships- (Summer after Semester 6, Semester 7/8 (during academic year))
Actively seek and complete internships at reputable tech companies (MNCs or top Indian startups). Focus on gaining hands-on industry experience and building professional networks.
Tools & Resources
IITK Career Development Centre (CDC), LinkedIn, company career portals
Career Connection
Often leads to pre-placement offers (PPOs) and provides crucial industry exposure for final placements.
Undertake a Substantial Thesis/Project- (Semester 7-10)
For the M.Tech component, choose a challenging thesis topic, conduct thorough research under faculty guidance, and aim for publishable work or innovative solutions.
Tools & Resources
IITK Library resources, research journals (ACM, IEEE), specialized software/hardware
Career Connection
Develops deep expertise, research skills, and problem-solving abilities, highly valued for R&D roles and further academic pursuits.
Prepare Strategically for Placements & Higher Studies- (Semester 7-10)
Refine interview skills, practice aptitude tests, prepare tailored resumes, and participate in mock interviews. Simultaneously, prepare for competitive exams like GATE if considering further M.Tech outside IITK or Ph.D. abroad.
Tools & Resources
Career Development Centre workshops, online mock interview platforms, GATE/GRE/TOEFL preparation materials
Career Connection
Maximizes chances of securing desired job roles or admissions to top graduate programs.
Program Structure and Curriculum
Eligibility:
- JEE Advanced rank
Duration: 10 semesters/ 5 years
Credits: 391 Credits
Assessment: Internal: undefined, External: undefined
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHY101 | Physics I | Core | 8 | Newtonian Mechanics, Rigid Body Dynamics, Lagrangian & Hamiltonian Mechanics, Special Relativity, Oscillations |
| MTH101 | Mathematics I | Core | 8 | Functions & Limits, Differentiation, Integration, Infinite Series, Multivariable Calculus Introduction |
| TA101 | Engineering Graphics | Core | 3 | Orthographic Projections, Isometric Drawings, Sectional Views, AutoCAD Basics, Dimensioning |
| LIF101 | Introduction to Life Sciences | Core | 6 | Cell Structure & Function, Genetics & Heredity, Evolution, Human Systems, Ecosystems |
| CHM101 | Chemistry I | Core | 8 | Atomic Structure, Chemical Bonding, Thermodynamics, Reaction Kinetics, Organic Chemistry Basics |
| TA102 | Workshop Practice | Core | 3 | Carpentry, Welding, Machining, Fitting, Sheet Metal Work, Foundry Practices |
| ESC101 | Introduction to Engineering | Core | 8 | Electrical Circuits, Basic Electronics, Sensors, Measurement Systems, Instrumentation |
| HSS | Humanities and Social Sciences Elective (HSS 1) | HSS Elective | 6 | Arts & Humanities, Social Sciences, Communication Skills, Critical Thinking, Ethical Studies |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHY102 | Physics II | Core | 8 | Electromagnetism, Optics, Quantum Mechanics, Solid State Physics, Nuclear Physics |
| MTH102 | Mathematics II | Core | 8 | Vector Calculus, Fourier Series, Partial Differential Equations, Complex Numbers, Laplace Transforms |
| ESC102 | Introduction to Computing | Core | 6 | Problem Solving, Algorithms, C Programming, Data Representation, Computer Architecture |
| ESC103 | Engineering Mechanics | Core | 8 | Statics, Dynamics, Rigid Body Kinematics, Work & Energy, Friction |
| ESC104 | Basic Electronics Lab | Core | 3 | Circuit Components, Breadboarding, Multimeter Usage, Oscilloscope, Logic Gates |
| CHM102 | Chemistry II | Core | 8 | Inorganic Chemistry, Organic Reactions, Physical Chemistry, Spectroscopy, Polymers |
| PE101 | Physical Education | Core | 0 | Sports, Fitness, Team Games, Yoga, Wellness |
| HSS | Humanities and Social Sciences Elective (HSS 2) | HSS Elective | 6 | Cultural Studies, Economic Principles, Political Science, Psychology, Sociological Theories |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS201 | Data Structures and Algorithms | Core | 8 | Arrays & Linked Lists, Trees & Graphs, Sorting & Searching, Hashing, Algorithm Analysis |
| CS202 | Discrete Mathematics | Core | 8 | Logic & Proofs, Set Theory, Combinatorics, Graph Theory, Recurrence Relations, Algebraic Structures |
| CS203 | Digital Logic and Design | Core | 8 | Boolean Algebra, Logic Gates, Combinational Circuits, Sequential Circuits, Memory |
| MTH203 | Linear Algebra and Differential Equations | Core | 8 | Vector Spaces, Matrices, Eigenvalues, Ordinary Differential Equations, Partial Differential Equations |
| SE | Science Elective I | Science Elective | 8 | Advanced Physics, Mathematical Methods, Scientific Computing, Statistical Methods |
| HSS | Humanities and Social Sciences Elective (HSS 3) | HSS Elective | 6 | Philosophy, Literature, History, Fine Arts, Linguistics |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS210 | Computer Organization | Core | 8 | ISA, CPU Design, Pipelining, Memory Hierarchy, I/O Organization, Parallelism |
| CS220 | Theory of Computation | Core | 8 | Automata Theory, Formal Languages, Computability, Decidability, Complexity Classes |
| CS230 | Operating Systems | Core | 8 | Process Management, Memory Management, File Systems, I/O Management, Concurrency |
| CS240 | Database Management Systems | Core | 8 | ER Modeling, Relational Algebra, SQL, Normalization, Transaction Management, Concurrency Control |
| HSS | Humanities and Social Sciences Elective (HSS 4) | HSS Elective | 6 | Ethics, Psychology, Sociology, Economics, Public Policy |
| SE | Science Elective II | Science Elective | 8 | Advanced Chemistry, Environmental Science, Biosciences, Materials Science |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS330 | Compiler Design | Core | 8 | Lexical Analysis, Parsing, Semantic Analysis, Code Generation, Optimization, Runtime Systems |
| CS340 | Computer Networks | Core | 8 | OSI Model, TCP/IP Suite, Routing Protocols, Congestion Control, Network Security, Wireless Networks |
| CS350 | Introduction to Machine Learning | Core | 8 | Supervised Learning, Unsupervised Learning, Regression, Classification, Neural Networks, Deep Learning |
| DE | Departmental Elective I | Departmental Elective | 6 | Advanced CSE Topics, Specialized Algorithms, Emerging Technologies, Software Engineering Principles |
| OE | Open Elective I | Open Elective | 6 | Interdisciplinary Studies, Non-CSE Fields, Management, Entrepreneurship |
| HSS | Humanities and Social Sciences Elective (HSS 5) | HSS Elective | 6 | History of Science, Philosophy of Mind, Global Politics, Anthropology |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS360 | Artificial Intelligence | Core | 8 | Problem Solving, Search Algorithms, Knowledge Representation, Logic, Planning, Machine Learning |
| CS370 | Algorithms | Core | 8 | Divide & Conquer, Dynamic Programming, Greedy Algorithms, Graph Algorithms, NP-Completeness |
| DE | Departmental Elective II | Departmental Elective | 6 | Advanced Data Science, Cybersecurity, Computer Graphics, Software Engineering |
| DE | Departmental Elective III | Departmental Elective | 6 | Distributed Systems, Parallel Computing, Natural Language Processing, Robotics |
| OE | Open Elective II | Open Elective | 6 | Financial Management, Design Thinking, Environmental Studies, Creative Writing |
| HSS | Humanities and Social Sciences Elective (HSS 6) | HSS Elective | 6 | Ethics in Technology, Psychology of Learning, Indian Society, Global Cultures |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS498 | Thesis Part I | Project/Thesis | 18 | Research Methodology, Literature Review, Problem Formulation, Initial Design, Experimental Setup |
| DE | Departmental Elective IV | Departmental Elective | 6 | Advanced Operating Systems, Network Security, Big Data Analytics, Cloud Computing |
| DE | Departmental Elective V | Departmental Elective | 6 | Image Processing, Bioinformatics, VLSI Design, Quantum Computing |
| OE | Open Elective III | Open Elective | 6 | Project Management, Entrepreneurship, Technical Communication, Foreign Language |
| HSS | Humanities and Social Sciences Elective (HSS 7) | HSS Elective | 6 | Public Speaking, Cross-Cultural Communication, Professional Ethics, Innovation & Creativity |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS499 | Thesis Part II | Project/Thesis | 18 | Data Collection & Analysis, Algorithm Implementation, Performance Evaluation, Result Interpretation, Thesis Writing |
| DE | Departmental Elective VI | Departmental Elective | 6 | Deep Learning, Computer Vision, Cryptography, Human-Computer Interaction |
| DE | Departmental Elective VII | Departmental Elective | 6 | Wireless Networks, Internet of Things, Formal Methods, Compilers & Programming Languages |
| OE | Open Elective IV | Open Elective | 6 | Intellectual Property Rights, Organizational Behavior, Marketing Fundamentals, Supply Chain Management |
| HSS | Humanities and Social Sciences Elective (HSS 8) | HSS Elective | 6 | Critical Thinking, Emotional Intelligence, Conflict Resolution, Leadership Skills |
Semester 9
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| ADE | Advanced Departmental Elective I | Departmental Elective (M.Tech) | 6 | Advanced Algorithms, Computational Geometry, Randomized Algorithms, Complexity Theory |
| ADE | Advanced Departmental Elective II | Departmental Elective (M.Tech) | 6 | Advanced Computer Architecture, Parallel Architectures, Memory Systems, Processor Design, Performance Evaluation |
| ADE | Advanced Departmental Elective III | Departmental Elective (M.Tech) | 6 | Advanced Database Systems, Distributed Databases, NoSQL, Data Warehousing, Query Processing |
| ADE | Advanced Departmental Elective IV | Departmental Elective (M.Tech) | 6 | Distributed Systems, Consensus Protocols, Fault Tolerance, Distributed Algorithms, Cloud Computing |
Semester 10
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| ADE | Advanced Departmental Elective V | Departmental Elective (M.Tech) | 6 | Parallel Computing, Parallel Programming Models, GPU Computing, Performance Optimization |
| ADE | Advanced Departmental Elective VI | Departmental Elective (M.Tech) | 6 | Cryptography, Public Key Cryptography, Digital Signatures, Hash Functions, Network Security |
