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B-TECH in Mathematics And Computing at Indian Institute of Technology Ropar
Rupnagar, Punjab
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About the Specialization
What is Mathematics and Computing at Indian Institute of Technology Ropar Rupnagar?
This B.Tech in Mathematics and Computing program at IIT Ropar provides a robust foundation in both theoretical mathematics and applied computer science. It focuses on developing strong analytical and computational skills, crucial for solving complex problems across various domains. The curriculum is designed to meet the growing demands of India''''s data-driven and technology-intensive industries, preparing students for innovative roles.
Who Should Apply?
This program is ideal for high-achieving students with a keen interest in mathematics and a passion for computing. It attracts fresh graduates seeking entry into cutting-edge fields like data science, artificial intelligence, quantitative finance, and scientific computing. Professionals looking to upskill in advanced mathematical modeling or algorithms will also find this program beneficial, as will career changers targeting analytical technology roles.
Why Choose This Course?
Graduates of this program can expect diverse and high-growth career paths in India as Data Scientists, AI Engineers, Machine Learning Specialists, Quantitative Analysts, Software Developers, and Research Scientists. Entry-level salaries typically range from 8-15 LPA, with experienced professionals earning upwards of 20-30 LPA. The program aligns with skills required for certifications in analytics, cloud computing, and financial modeling, fostering significant professional advancement.
Student Success Practices
Foundation Stage
Master Programming Fundamentals- (Semester 1-2)
Develop a strong proficiency in programming languages like C, C++, and Python. Regularly solve problems on platforms such as HackerRank, LeetCode, and CodeChef to solidify understanding of data structures and algorithms.
Tools & Resources
HackerRank, LeetCode, CodeChef, GeeksforGeeks
Career Connection
Excelling in competitive programming directly enhances performance in technical coding interviews for top tech companies during placements.
Build Strong Mathematical Foundations- (Semester 1-2)
Focus intently on core mathematical subjects like Calculus, Linear Algebra, and Discrete Mathematics. Utilize supplementary resources like NPTEL courses and online tutorials to deepen conceptual understanding.
Tools & Resources
NPTEL, MIT OpenCourseware, Khan Academy
Career Connection
A robust mathematical background is indispensable for advanced M&C courses, machine learning, and quantitative finance roles, boosting problem-solving abilities.
Engage in Peer Learning and Study Groups- (Semester 1-2)
Form study groups with classmates to discuss challenging topics, solve assignments collaboratively, and prepare for exams. Actively participate in academic discussions and review sessions.
Tools & Resources
Campus study rooms, Online collaboration tools
Career Connection
Improves understanding, communication, and teamwork skills, which are highly valued in corporate environments for collaborative project work.
Intermediate Stage
Apply Knowledge through Personal Projects- (Semester 3-5)
Initiate and complete personal coding projects using learned data structures, algorithms, and object-oriented programming principles. Document and showcase these projects on platforms like GitHub.
Tools & Resources
GitHub, Jupyter Notebooks, VS Code
Career Connection
Demonstrates practical application of theoretical knowledge to recruiters, providing tangible evidence of skills during internship and placement interviews.
Seek Industry Exposure via Internships- (Semester 3-5)
Actively apply for summer internships in relevant fields such as data science, software development, or quantitative analysis at Indian startups or established MNCs operating in India.
Tools & Resources
LinkedIn, Internshala, Company career pages
Career Connection
Provides invaluable real-world experience, helps build professional networks, and often leads to pre-placement offers, accelerating career entry.
Participate in Coding Competitions and Hackathons- (Semester 3-5)
Regularly participate in national and international coding contests (e.g., Google Kick Start, Code Jam) and hackathons organized by colleges or companies. These events sharpen problem-solving skills under pressure.
Tools & Resources
CodeChef, HackerEarth, Devpost
Career Connection
Develops quick thinking, innovative problem-solving, and teamwork, highly attractive traits for tech recruiters and competitive roles.
Advanced Stage
Specialized Skill Development- (Semester 6-8)
Deep dive into specialized areas aligned with career interests, such as Machine Learning, Deep Learning, Financial Mathematics, or Cryptography. Complete advanced online courses or certifications in these domains.
Tools & Resources
Coursera, edX, Udacity, NPTEL Advanced Courses
Career Connection
Creates a distinct competitive advantage, making students highly marketable for niche roles in rapidly evolving tech and finance sectors in India.
Intensive Placement Preparation- (Semester 6-8)
Engage in rigorous preparation for aptitude tests, technical interviews (covering data structures, algorithms, system design), and HR rounds. Participate in mock interviews and resume-building workshops.
Tools & Resources
Placement cells, Mock interview platforms, Online aptitude tests
Career Connection
Maximizes chances of securing placements in top-tier technology, finance, and analytics firms by ensuring readiness for all stages of the recruitment process.
Engage in Research and Capstone Projects- (Semester 6-8)
Undertake significant research projects under faculty mentorship or pursue a challenging capstone project. Aim for publication in conferences or journals to showcase advanced research capabilities.
Tools & Resources
Research labs, Academic journals, Conference proceedings
Career Connection
Develops critical thinking, research acumen, and problem-solving at a higher level, essential for R&D roles, academia, or entrepreneurial ventures in India and globally.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 (or equivalent) with Physics, Chemistry, and Mathematics with at least 75% aggregate marks (or 65% for SC/ST/PwD) and qualified JEE Advanced.
Duration: 8 semesters / 4 years
Credits: 157 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| HS101 | Introduction to Professional Communication | Core | 3 | Basic English Grammar, Reading Comprehension, Public Speaking, Group Discussion, Professional Writing |
| PH101 | Physics | Core | 4 | Relativistic Mechanics, Quantum Mechanics, Solid State Physics, Lasers and Optics, Nuclear Physics |
| PH102 | Physics Lab | Lab | 1 | Error Analysis, Experiments on Optics, Electricity and Magnetism, Quantum Phenomena, Semiconductor Devices |
| MA101 | Mathematics-I | Core | 4 | Differential Calculus, Integral Calculus, Sequences and Series, Multivariable Calculus, Vector Calculus |
| BT101 | Biology for Engineers | Core | 2 | Introduction to Biology, Cell Biology, Genetics, Metabolism, Bioengineering Applications |
| ES101 | Introduction to Programming | Core | 3 | Programming Fundamentals, Data Types and Operators, Control Structures, Functions, Arrays and Pointers |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CY101 | Chemistry | Core | 4 | Chemical Bonding, Thermodynamics, Electrochemistry, Organic Chemistry, Spectroscopic Techniques |
| CY102 | Chemistry Lab | Lab | 1 | Volumetric Analysis, Gravimetric Analysis, pH Metry, Conductometry, Synthesis of Organic Compounds |
| CS101 | Data Structures and Algorithms | Core | 4 | Arrays and Linked Lists, Stacks and Queues, Trees and Graphs, Searching and Sorting Algorithms, Hashing |
| ES102 | Introduction to Engineering Graphics | Core | 2 | Orthographic Projections, Isometric Projections, Sections of Solids, Development of Surfaces, CAD Tools |
| ES103 | Engineering Mechanics | Core | 4 | Statics of Particles, Equilibrium of Rigid Bodies, Friction, Kinematics of Particles, Dynamics of Rigid Bodies |
| MA102 | Mathematics-II | Core | 4 | Differential Equations, Laplace Transforms, Fourier Series, Partial Differential Equations, Complex Analysis Introduction |
| EV101 | Environmental Studies | Core | 1 | Natural Resources, Ecosystems, Environmental Pollution, Social Issues and Environment, Environmental Management |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS201 | Discrete Mathematics | Core | 4 | Logic and Proofs, Set Theory, Relations and Functions, Combinatorics, Graph Theory |
| MA201 | Linear Algebra | Core | 4 | Vector Spaces, Linear Transformations, Eigenvalues and Eigenvectors, Inner Product Spaces, Matrix Decompositions |
| EE201 | Basic Electronics Engineering | Core | 4 | Semiconductor Devices, Diode Circuits, Transistor Biasing, Amplifiers, Operational Amplifiers |
| MA202 | Probability and Statistics | Core | 4 | Probability Axioms, Random Variables, Probability Distributions, Hypothesis Testing, Regression Analysis |
| CS202 | Object Oriented Programming | Core | 4 | Classes and Objects, Inheritance, Polymorphism, Abstraction, Exception Handling |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA203 | Abstract Algebra | Core | 4 | Groups, Rings, Fields, Homomorphisms, Polynomial Rings |
| CS203 | Theory of Computation | Core | 4 | Finite Automata, Regular Languages, Context-Free Grammars, Turing Machines, Undecidability |
| MA204 | Real Analysis | Core | 4 | Metric Spaces, Sequences and Series of Functions, Riemann Integration, Lebesgue Measure, Fourier Analysis |
| HS201 | Economics | Core | 3 | Microeconomics Principles, Macroeconomics Overview, Market Structures, National Income Accounting, Fiscal and Monetary Policy |
| CS204 | Operating Systems | Core | 4 | Process Management, CPU Scheduling, Memory Management, File Systems, I/O Systems, Concurrency |
| ES201 | Manufacturing Practices | Core | 2 | Machining Processes, Welding Techniques, Forming Operations, Foundry Practices, Carpentry Skills, Metrology |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA301 | Complex Analysis | Core | 4 | Complex Numbers, Analytic Functions, Contour Integration, Series Expansions, Conformal Mappings |
| MA302 | Numerical Methods | Core | 4 | Error Analysis, Solutions of Equations, Interpolation Techniques, Numerical Differentiation and Integration, Ordinary Differential Equations |
| CS301 | Database Management Systems | Core | 4 | Relational Model, SQL Query Language, ER Modeling, Normalization, Transaction Management, Concurrency Control |
| CS302 | Computer Networks | Core | 4 | Network Layers, TCP/IP Protocol Suite, Routing Algorithms, Congestion Control, Application Layer Protocols |
| Elective-I | Elective-I | Elective | 3 | |
| Elective-II | Elective-II | Elective | 3 |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA303 | Topology | Core | 4 | Topological Spaces, Open and Closed Sets, Continuity, Connectedness, Compactness |
| MA304 | Functional Analysis | Core | 4 | Normed Spaces, Banach Spaces, Hilbert Spaces, Linear Operators, Dual Spaces |
| CS303 | Artificial Intelligence | Core | 4 | Search Algorithms, Knowledge Representation, Machine Learning Basics, Neural Networks, Natural Language Processing |
| CS304 | Compiler Design | Core | 4 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| Elective-III | Elective-III | Elective | 3 | |
| Elective-IV | Elective-IV | Elective | 3 |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA401 | Optimization Techniques | Core | 4 | Linear Programming, Simplex Method, Duality Theory, Non-linear Programming, Integer Programming |
| CS401 | Machine Learning | Core | 4 | Supervised Learning, Unsupervised Learning, Deep Learning Introduction, Reinforcement Learning, Model Evaluation |
| Project-I | Project-I | Project | 3 | Project Management, Literature Survey, Problem Definition, System Design, Initial Implementation |
| Elective-V | Elective-V | Elective | 3 | |
| Elective-VI | Elective-VI | Elective | 3 |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA402 | Financial Mathematics | Core | 4 | Interest Rates and Bonds, Derivatives Pricing, Option Pricing Models, Stochastic Processes in Finance, Portfolio Optimization |
| CS402 | Cryptography | Core | 4 | Symmetric Key Cryptography, Asymmetric Key Cryptography, Hashing and Message Authentication, Digital Signatures, Network Security Protocols |
| Project-II | Project-II | Project | 4 | Advanced System Development, Testing and Validation, Comprehensive Documentation, Technical Presentation, Final Project Report |
| Elective-VII | Elective-VII | Elective | 3 | |
| Elective-VIII | Elective-VIII | Elective | 3 |
