The Indian Institute of Technology (IITs) has launched a new undergraduate engineering course in Mathematics and computing to keep up with the demand for computer graduates with strong mathematical skills.
This 4 year BTech Course in mathematics and computing will consist of 40% Mathematics, 30% core CS and 30% AI-related courses.
The new Btech course is designed to meet the needs of mathematics in scientific investigations and recent technological innovations. The curriculum is designed in such a way that this programme provides a perfect platform for those who seek strong mathematical and analytical components with a specialization in artificial intelligence.
BTech Mathematics and Computing Course Structure (Semester-wise)
Semester – 1
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | MA101 | Calculus | 3 |
2. | HS103 or HS102 | Professional English Communication(HS103) or English Language Skills(HS102) | 3 |
3. | NC101 | NCC I | 1 |
4. | CY101 | Chemistry for Engineers | 4 |
5. | GE103 | Introduction to Computer Programming & Data Structure | 4.5 |
6. | GE105 | Engineering Drawing | 1.5 |
7. | HS101 | History of Technology | 1.5 |
Total Credits | 18.5 |
Semester – 2
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | MA102 | Linear Algebra, Integral Transforms and Special Functions | 3 |
2. | MAXXY or MAXXZ | Program Core (3 ) or Program-Specific General Engineering | 3 |
3. | NC102 or NO102 or NS102 | NCC II or NSO II or NSS II | 1 |
4. | PH101 | Physics for Engineers | 5 |
5. | GE104 | Introduction to Electrical Engineering | 3 |
6. | GE102 | Workshop Practice | 2 |
7. | GE101 | Technology Museum Lab | 1 |
Total Credits | 18 |
Semester- 3
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | CS201 | Data Structures | 4 |
2. | MA411 | Real Analysis | 3 |
3. | MA201 | Differential Equations | 3 |
4. | EE201 | Signals and Systems | 3 |
5. | NCIII/NOIII/NSIII | NCC/NSO/NSS | 1 |
6. | HS201 / GE108 | Economics / Basic Electronics | 3 / 3 |
7. | GE107 / GE109 | Tinkering Lab / Introduction to Engineering Products | 1.5/ 1 |
Total Credits | 18 or 18.5 |
Semester- 4
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | MA204 | Introduction to Numerical Analysis | 3 |
2. | MA426 | Theory of computation | 3 |
3. | MA205 | Computing Lab | 2 |
4. | MA202 | Probability and Statistics | 3 |
5. | HS202 / BM101 | Human Geography and Societal Needs / Biology for Engineers | 3 / 3 |
6. | NCIV/NOIV/NSIV | NCC/NSO/NSS | 1 |
7. | HS201 / GE108 | Economics/ Basic Electronics | 3 / 3 |
8. | GE107 / GE109 | Tinkering Lab / Introduction to Engineering Products | 1.5 / 1 |
Total Credits | 19 or 19.5 |
Semester- 5
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | MA514 | Analysis & Design of Algorithms | 3 |
2. | MA515 | Foundations of Data Science | 4 |
3. | MA301 | Computational Algebra | 3 |
4. | HS202 / BM101 | Human Geography and Societal Needs / Biology for Engineers | 3 / 3 |
5. | HS301 / GE111 | Industrial Management / Introduction to Environmental Science & Engineering | 3 |
6. | HS104 | Professional Ethics [about 50% students] | 1.5 |
Total Credits | 16 or 17.5 |
Semester- 6
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | MA302 | Optimization Techniques | 3 |
2. | MA303 | Computing Lab-II | 2 |
3. | CS503 | Machine Learning | 4 |
4. | CP301 | Development Engineering Project | 3 |
5. | HS301 / GE111 | Industrial Management / Introduction to Environmental Science & Engineering | 3 |
6. | HS104 | Professional Ethics [about 50% students] | 1.5 |
Total Credits | |||
Summer Vacation following Semester 6 | |||
Sr. | Course Code | Course Name | Credits |
1. | II301 | Industrial Internship and Comprehensive Viva Voce (70% weightage for 8-week full internship and 30% for comprehensive viva on program fundamentals) | 3.5 |
Total Credits | 3.5 |
Semester- 7
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | CP302 | Capstone Project I | 3 |
ELECTIVE COURSES | |||
2. | HSXXX | An English Language/Literature elective course in either 7th or 8th sem for students who had “English Language Skills” in 1st Semester | 3 |
3. | BMXXX /MAXXX /CYXXX /PHXXX | Science Maths Elective I | 3 |
4. | MAXXX | Program Elective I | 3 |
5. | XXXXX | Any extra credits taken under HS Elective /Program Elective/Science Maths Elective | 3 |
Total Credits | 15 Credits |
Semester- 8
Sr. | Course Code | Course Name | Credits |
---|---|---|---|
1. | CP303 | Capstone Project II | 3 |
ELECTIVE COURSES | |||
2. | HSXXX | An English Language/Literature elective course in either 7th or 8th sem for students who had “English Language Skills” in 1st Semester | 3 |
3. | BMXXX /MAXXX /CYXXX /PHXXX | Science Maths Elective II | 3 |
4. | MAXXX | Program Elective II | 3 |
5. | XXXXX | Any extra credits taken under HS Elective /Program Elective/Science Maths Elective | 3 |
Total Credits | 15 Credits |
Admission to all three programmes will be done on the basis of JEE Advanced score. Additionally, candidates must have completed class 12 (or equivalent) examination from any recognised state or central board.
BTech in Mathematics and Computing Elective Subjects
- Foundation of Data Science
- Data Mining
- Deep Learning
- Finance Mathematics
- Time Series Analysis
- Graph Theory
- Number Theory & Cryptography
- Functional Analysis
- Computational Partial Differential Equations
- Randomized Algorithms
- Game Theory
- Stochastic Process and Monte Carlo Simulation
- Applied Statistics
- Operating systems
- Data Base Management System
- Computer Architecture
- Approximation Algorithm
- Fuzzy Logic & Application
- Matrix Computation
- Applied Linear Algebra
- Complex Analysis
- Dynamical Systems
- Artificial Intelligence
- Algorithmic graph theory
- Combinatorial optimization
- Graphical Models
- Computer Vision
- Network Science
- Computational PDE
- Computational Fluid Dynamics
- Fluid Dynamics
- Advanced Data Structures
BTech in Mathematics and Computing – Career Prospects
Studies from IIT state that graduates of BTech in Mathematics and Computing will get great career opportunities in companies related to information technology, banking & finance, and machine learning-assisted technologies.