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B-TECH in Mathematics And Computing at Indian Institute of Technology Indore
Indore, Madhya Pradesh
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About the Specialization
What is Mathematics and Computing at Indian Institute of Technology Indore Indore?
This Mathematics and Computing program at Indian Institute of Technology Indore focuses on blending rigorous mathematical foundations with advanced computational techniques. It prepares students for cutting-edge careers in fields driven by data, algorithms, and complex modeling. The interdisciplinary nature addresses the growing demand in the Indian market for professionals who can innovate across diverse technological domains, from finance to AI. The program emphasizes problem-solving and analytical thinking.
Who Should Apply?
This program is ideal for high-achieving fresh graduates who have excelled in JEE Advanced and possess a strong aptitude for both mathematics and computer science. It caters to those aspiring for careers in quantitative finance, data science, machine learning, scientific computing, and research. Individuals passionate about developing robust algorithms, building intelligent systems, and solving intricate computational problems will find this specialization highly rewarding.
Why Choose This Course?
Graduates of this program can expect to secure high-value roles in India-specific career paths such as Data Scientist, Machine Learning Engineer, Quantitative Analyst, Algorithm Developer, or Scientific Computing Specialist. Entry-level salaries typically range from INR 10-25 LPA, with significant growth trajectories in leading Indian and multinational tech, finance, and research firms. The curriculum also prepares students for advanced studies and research opportunities globally.
Student Success Practices
Foundation Stage
Master Programming and Mathematical Foundations- (Semester 1-2)
Dedicate time to thoroughly understand core concepts in calculus, linear algebra, discrete mathematics, and C++/Python programming. Utilize online platforms like HackerRank and CodeChef for competitive programming to sharpen logical thinking and coding skills. Form study groups to solve complex problems and review concepts collaboratively, building a strong base for advanced courses.
Tools & Resources
NPTEL courses for theoretical concepts, GeeksforGeeks for problem solving, LeetCode for algorithm practice, Campus coding clubs
Career Connection
A strong foundation in these areas is crucial for all subsequent courses and is a primary filter in technical interviews for software development and data science roles.
Develop Strong Problem-Solving Acumen- (Semester 1-2)
Engage actively with challenging problems presented in assignments and tutorials across mathematics and computing subjects. Participate in college-level math olympiads or programming contests. Learn to break down complex problems into smaller, manageable parts and apply appropriate algorithms or mathematical techniques to find efficient solutions.
Tools & Resources
Textbooks recommended by faculty, Problem sets from previous years, Online math puzzles and logic games
Career Connection
Employers highly value analytical and problem-solving skills, which are critical for innovation and overcoming real-world technical challenges.
Cultivate Effective Time Management and Study Habits- (Semester 1-2)
Establish a consistent study schedule, balancing theory, practical lab work, and extracurricular activities. Prioritize tasks using techniques like the Pomodoro method or Eisenhower Matrix. Regular revisions and concept mapping will aid in retention. Seek feedback from professors during office hours to clarify doubts promptly.
Tools & Resources
Google Calendar/Planner for scheduling, Note-taking apps like Notion or OneNote, Campus counseling services for academic guidance
Career Connection
Good academic performance and efficient work habits developed early on contribute directly to better internship and placement opportunities.
Intermediate Stage
Dive Deep into Data Structures and Algorithms- (Semester 3-5)
Beyond classroom learning, practice implementing various data structures and algorithms extensively. Solve a wide range of problems on platforms like LeetCode, HackerRank, and TopCoder. Understand the time and space complexity trade-offs for different approaches. Participate in IIT Indore''''s competitive programming events and mock interviews.
Tools & Resources
LeetCode premium, Codeforces, InterviewBit, Past placement papers
Career Connection
Proficiency in DSA is a non-negotiable requirement for tech placements, especially for software development and algorithm-focused roles in Indian and global firms.
Seek Early Industry Exposure via Internships and Projects- (Semester 3-5)
Actively search for summer internships (even short-term ones) or work on self-initiated projects in areas like machine learning, data science, or scientific computing. Collaborate with faculty on research projects. This practical exposure helps apply theoretical knowledge, build a portfolio, and network with professionals in the Indian industry.
Tools & Resources
Internshala, LinkedIn for internships, GitHub for project showcasing, Faculty research opportunities
Career Connection
Early practical experience significantly boosts employability, provides clarity on career paths, and often leads to pre-placement offers in top companies.
Specialize and Explore Advanced Concepts- (Semester 3-5)
Identify areas of interest within Mathematics and Computing, such as AI, ML, Optimization, or Theoretical Computer Science. Take relevant departmental electives and enroll in MOOCs from platforms like Coursera or edX to gain specialized knowledge. Attend workshops and seminars at IIT Indore related to your chosen specialization.
Tools & Resources
Coursera, edX, Udacity for specialized courses, Reading research papers (arXiv, Google Scholar), Departmental clubs and societies
Career Connection
Developing niche skills makes you a more attractive candidate for specialized roles and advanced research opportunities in a competitive Indian job market.
Advanced Stage
Focus on Capstone Projects and Research- (Semester 6-8)
Invest deeply in your final year projects (Project I and II) by choosing challenging, industry-relevant problems or contributing to ongoing research. Aim for publications in conferences or journals if pursuing research. Showcase these projects prominently in your resume and portfolio, demonstrating your ability to deliver substantial work.
Tools & Resources
Jupyter notebooks, Google Colab, TensorFlow, PyTorch, SciPy, LaTeX for technical writing, Mendeley for reference management
Career Connection
High-quality projects are often the deciding factor in placements, especially for R&D, data science, and ML engineering roles, showcasing practical expertise.
Intensive Placement and Interview Preparation- (Semester 6-8)
Begin placement preparation early by revising core computer science and mathematics subjects. Practice aptitude tests, group discussions, and technical interviews. Participate in mock interview sessions organized by the career cell or student bodies. Tailor your resume and cover letter for specific roles, highlighting relevant skills and projects.
Tools & Resources
Placement cell resources, Mock interview platforms, Company-specific interview guides, Networking with alumni
Career Connection
Thorough preparation directly translates into successful placements, helping secure positions in top-tier companies across India''''s tech and finance sectors.
Build Professional Network and Soft Skills- (Semester 6-8)
Attend industry conferences, guest lectures, and alumni meets to expand your professional network. Develop crucial soft skills like communication, teamwork, and leadership through participation in student clubs, organizing events, and leading project teams. These skills are vital for career progression in any Indian organization.
Tools & Resources
LinkedIn for professional networking, Toastmasters club for public speaking, College clubs and committees
Career Connection
A strong network and polished soft skills are essential for navigating corporate environments, securing future opportunities, and advancing into leadership roles.
Program Structure and Curriculum
Eligibility:
- Admission is purely based on the rank obtained in JEE (Advanced) examination.
Duration: 8 semesters / 4 years
Credits: 189 Credits
Assessment: Internal: Instructor decided, typically Mid-semester 20%-30% weightage (Quizzes, assignments, and projects also contribute), External: Instructor decided, End-semester examination normally 40%-50% weightage
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA101 | Calculus | Core | 4 | Real Numbers and Functions, Sequences and Series, Functions of Several Variables, Partial Derivatives and Applications, Multiple Integrals and Vector Calculus |
| CS101 | Introduction to Computing | Core | 4 | Introduction to Computers and Programming, C++ Programming Fundamentals, Control Structures and Functions, Arrays, Pointers, and Strings, Structures, Unions, and File I/O |
| EE101 | Electrical Sciences | Core | 4 | DC and AC Circuits, Network Theorems and Resonance, Magnetic Circuits and Transformers, Electrical Machines (DC and AC), Semiconductor Diodes and Transistors |
| PH101 | Physics - I | Core | 4 | Classical Mechanics, Special Theory of Relativity, Oscillations and Waves, Interference and Diffraction, Introduction to Quantum Mechanics |
| BT101 | Introduction to Biosciences | Core | 3 | Introduction to Biological Systems, Cell Biology and Metabolism, Genetics and Molecular Biology, Immune System and Pathogens, Applications of Biotechnology |
| HS101 | English Communication | Humanities Core | 3 | Fundamentals of Communication, Listening and Speaking Skills, Reading Comprehension Strategies, Academic and Professional Writing, Presentation Techniques |
| HS102 | Psychology | Humanities Core | 3 | Introduction to Psychology, Cognition and Learning, Motivation, Emotion, and Stress, Personality Theories, Social Psychology and Group Dynamics |
| PH102 | Physics Lab - I | Lab | 2 | Measurements and Error Analysis, Experiments on Oscillations and Waves, Optics Experiments, Electricity and Magnetism Experiments, Modern Physics Demonstrations |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA102 | Linear Algebra | Core | 4 | Vector Spaces and Subspaces, Linear Transformations, Eigenvalues and Eigenvectors, Inner Product Spaces and Orthogonality, Diagonalization and Quadratic Forms |
| CS102 | Data Structures & Algorithms | Core | 4 | Introduction to Data Structures, Arrays, Linked Lists, Stacks, Queues, Trees and Heaps, Graphs and Graph Algorithms, Sorting, Searching, and Hashing |
| EE102 | Digital Systems & Microcontrollers | Core | 4 | Boolean Algebra and Logic Gates, Combinational Logic Circuits, Sequential Logic Circuits, Registers, Counters, and Memory, Microprocessor and Microcontroller Basics |
| CH101 | Chemistry | Core | 4 | Atomic Structure and Bonding, Thermodynamics and Chemical Equilibrium, Electrochemistry and Reaction Kinetics, Coordination Chemistry, Organic Chemistry Fundamentals |
| CH102 | Chemistry Lab | Lab | 2 | Quantitative Analysis Techniques, Volumetric and Gravimetric Analysis, Organic Synthesis Experiments, Spectroscopic Methods, Physical Chemistry Experiments |
| EG101 | Engineering Graphics & Drawing | Core | 3 | Principles of Engineering Graphics, Orthographic Projections, Isometric Projections, Sectional Views and Developments, Introduction to CAD Software |
| HS103 | Introductory Sociology | Humanities Core | 3 | Introduction to Sociological Perspective, Culture and Socialization, Social Stratification and Inequality, Social Institutions (Family, Education), Social Change and Development |
| HS104 | Introduction to Economics | Humanities Core | 3 | Basic Economic Concepts, Microeconomics: Supply, Demand, Markets, Macroeconomics: National Income, Inflation, Fiscal and Monetary Policy, International Trade and Globalization |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA201 | Probability and Statistics | Core | 4 | Axioms of Probability, Random Variables and Distributions, Joint and Conditional Distributions, Sampling Distributions and Estimation, Hypothesis Testing and Regression |
| CS201 | Design and Analysis of Algorithms | Core | 4 | Algorithm Analysis and Complexity, Divide and Conquer Algorithms, Greedy Algorithms and Dynamic Programming, Graph Algorithms (Traversal, Shortest Paths), NP-Completeness and Approximation Algorithms |
| MA202 | Numerical Analysis | Core | 4 | Error Analysis and Machine Arithmetic, Solution of Nonlinear Equations, Interpolation and Polynomial Approximation, Numerical Differentiation and Integration, Numerical Solutions of ODEs |
| CS202 | Object Oriented Programming | Core | 4 | Introduction to OOP Concepts, Classes, Objects, Constructors, Inheritance and Polymorphism, Abstract Classes and Interfaces, Exception Handling and Templates |
| EL201 | Electronics Lab | Lab | 4 | Experiments with Diodes and Transistors, Operational Amplifiers and their Applications, Combinational Logic Design, Sequential Logic Design, Microcontroller Programming |
| DE1 | Departmental Elective I | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MA203 | Numerical Analysis Lab | Lab | 2 | Implementation of Root Finding Methods, Programming Interpolation Techniques, Numerical Integration and Differentiation, Solving Ordinary Differential Equations, Error Analysis in Computation |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA204 | Differential Equations | Core | 4 | First Order Differential Equations, Higher Order Linear ODEs, Laplace Transforms, Series Solutions of ODEs, Partial Differential Equations |
| CS203 | Operating Systems | Core | 4 | Operating System Concepts and Structure, Process Management and Scheduling, Deadlocks and Concurrency, Memory Management Techniques, File Systems and I/O Management |
| CS204 | Database Management Systems | Core | 4 | Database System Architecture, Relational Model and Algebra, Structured Query Language (SQL), ER Modeling and Normalization, Transaction Management and Concurrency Control |
| HS201 | Professional Ethics | Humanities Core | 3 | Ethical Theories and Dilemmas, Engineering Ethics and Codes of Conduct, Corporate Social Responsibility, Intellectual Property Rights, Cyber Ethics and Privacy |
| EL202 | Data Communication | Core | 4 | Data Transmission Fundamentals, Network Models (OSI and TCP/IP), Error Detection and Correction, Flow Control and Medium Access, Networking Devices and Protocols |
| DE2 | Departmental Elective II | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MA205 | Differential Equations Lab | Lab | 2 | Numerical Methods for ODEs, Solving Boundary Value Problems, Introduction to Finite Difference Methods, Mathematical Modeling with ODEs, Simulation of Dynamic Systems |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA301 | Complex Analysis | Core | 4 | Complex Numbers and Functions, Analytic Functions and Cauchy-Riemann Equations, Complex Integration and Residues, Series Expansions (Taylor and Laurent), Conformal Mappings and Applications |
| CS301 | Theory of Computation | Core | 4 | Finite Automata and Regular Languages, Context-Free Grammars and Pushdown Automata, Turing Machines and Computability, Decidability and Undecidability, Complexity Classes (P, NP) |
| MN301 | Optimization Techniques | Core | 4 | Introduction to Optimization, Linear Programming and Simplex Method, Duality and Sensitivity Analysis, Unconstrained Nonlinear Optimization, Constrained Nonlinear Optimization |
| OE1 | Open Elective I | Elective | 3 | Interdisciplinary topics from other departments, Skills-based course, Management or entrepreneurship studies, Arts, culture, or social sciences, Language or communication skills |
| DE3 | Departmental Elective III | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| DE4 | Departmental Elective IV | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MA302 | Complex Analysis Lab | Lab | 2 | Visualization of Complex Functions, Conformal Mapping Implementations, Numerical Integration in Complex Plane, Solving Engineering Problems using Complex Analysis, Software tools for Complex Analysis |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA303 | Discrete Mathematics | Core | 4 | Mathematical Logic and Proof Techniques, Set Theory, Relations, and Functions, Combinatorics and Counting Principles, Graph Theory and Algorithms, Algebraic Structures and Coding Theory |
| CS302 | Computer Networks | Core | 4 | Network Models (OSI, TCP/IP), Physical Layer and Data Link Layer, Network Layer and Routing Protocols, Transport Layer (TCP, UDP), Application Layer Protocols (HTTP, DNS) |
| MN302 | Introduction to Machine Learning | Core | 4 | Fundamentals of Machine Learning, Supervised Learning: Regression and Classification, Unsupervised Learning: Clustering and PCA, Neural Networks and Deep Learning Basics, Model Evaluation and Hyperparameter Tuning |
| MN303 | Data Mining | Core | 4 | Introduction to Data Mining, Data Preprocessing and Exploration, Association Rule Mining, Classification Algorithms (Decision Trees, SVM), Clustering Techniques (K-means, Hierarchical) |
| OE2 | Open Elective II | Elective | 3 | Interdisciplinary topics from other departments, Skills-based course, Management or entrepreneurship studies, Arts, culture, or social sciences, Language or communication skills |
| DE5 | Departmental Elective V | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MA304 | Discrete Mathematics Lab | Lab | 2 | Implementation of Logic and Set Operations, Graph Algorithms and their Applications, Combinatorial Problem Solving, Boolean Algebra and Circuits, Introduction to Formal Language Tools |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA401 | Functional Analysis | Core | 4 | Metric Spaces and Topological Spaces, Normed Linear Spaces and Banach Spaces, Hilbert Spaces and Orthonormal Bases, Linear Operators and Functionals, Spectral Theory and Compact Operators |
| MN401 | Scientific Computing | Core | 4 | Numerical Linear Algebra, Iterative Methods for Linear Systems, Numerical Solutions of PDEs (Finite Difference), Finite Element Method Fundamentals, Scientific Visualization and Data Analysis |
| MN402 | Applied Statistics | Core | 4 | Statistical Inference and Hypothesis Testing, ANOVA and Experimental Design, Regression Analysis (Linear and Non-linear), Time Series Analysis, Non-parametric Methods and Bayesian Statistics |
| OE3 | Open Elective III | Elective | 3 | Interdisciplinary topics from other departments, Skills-based course, Management or entrepreneurship studies, Arts, culture, or social sciences, Language or communication skills |
| DE6 | Departmental Elective VI | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MN403 | Project - I | Project | 2 | Problem Identification and Literature Survey, Methodology and Design Specification, Preliminary Implementation and Experimentation, Data Collection and Analysis, Technical Report Writing and Presentation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MN404 | Project - II | Project | 4 | Advanced System Design and Implementation, Rigorous Testing and Validation, Detailed Results Analysis and Interpretation, Refinement of Research Methodology, Comprehensive Project Report and Defense |
| MN405 | Industrial Training/Internship | Project/Internship | 4 | Real-world Industry Exposure, Application of Theoretical Knowledge, Problem-Solving in a Corporate Environment, Professional Skill Development, Internship Report and Presentation |
| OE4 | Open Elective IV | Elective | 3 | Interdisciplinary topics from other departments, Skills-based course, Management or entrepreneurship studies, Arts, culture, or social sciences, Language or communication skills |
| OE5 | Open Elective V | Elective | 3 | Interdisciplinary topics from other departments, Skills-based course, Management or entrepreneurship studies, Arts, culture, or social sciences, Language or communication skills |
| DE7 | Departmental Elective VII | Elective | 3 | Selected topics from advanced Mathematics, Advanced topics in Computer Science, Specialized interdisciplinary areas, Research-oriented subject, Emerging technology concepts |
| MN406 | Seminar | Seminar | 2 | Literature Review and Topic Selection, Structuring and Delivering Technical Presentations, Effective Communication of Research, Critical Analysis and Peer Feedback, Answering Technical Questions |
