Tentative Curriculum for MnC Program(Subject to Approval)
(This Curriculum is based on the proposal discussed in the Academic Senate and is currently under review for formal approval by the Institute's Board of Governors.)
All Semesters
The B.Tech in Mathematics & Computing program is spread across 8 semesters. Each semester consists of a carefully designed set of courses that build upon the knowledge gained in previous semesters. Below is the detailed semester-wise course structure.
Legend
IC: Institute Core
DC: Departmental Core
DE: Departmental Elective
OE: Open Elective
| Course Code | Course Title | L-T-P (Credits) | Category |
|---|---|---|---|
| IC1101 | Calculus | 3-1-0 (4) | IC |
| IC1102 | General Chemistry | 3-1-0 (4) | IC |
| IC1103 | Engineering Mechanics | 3-1-0 (4) | IC |
| IC1104 | Introduction to Materials | 3-0-0 (3) | IC |
| IC1105 | Engineering Graphics | 1-0-3 (3) | IC |
| IC1106 | English for Communication | 1-0-2 (2) | IC |
| IC1107 | Electrical Technology | 2-0-0 (2) | IC |
| IC1108 | Basic Electronics | 2-0-0 (2) | IC |
| IC1109 | Chemistry Lab | 0-0-3 (3) | IC |
Available Electives
Students can choose from a wide range of departmental and open electives to customize their learning experience according to their interests and career goals.
Departmental Electives (DE)
- • Mathematical foundations of AI
- • Multivariate Calculus & Measure Theory
- • Convex Optimization
- • Computational Methods for Differential Equations
- • Functional Analysis
- • Computational Number Theory
- • Stochastic Models
- • Mathematical Modelling and Numerical Simulation
- • Financial Mathematics
- • Mathematical Image Processing
- • Statistical Simulation & Data Analysis
- • Computational Biology
- • Applied Functional Analysis
- • Compressed Sensing
- • Numerical Linear Algebra
- • Numerical Methods for Hyperbolic Problems
- • Abstract Algebra
- • Statistical Learning: Theory and Applications
Open Electives (OE)
- • High-Performance Computing
- • Image Processing
- • Operational Research
- • Signals & Systems
- • Time Series Analysis
- • Stochastic Processes
- • Bioinformatics
- • Probability & Computing
- • Combinatorial optimization
- • Partial Differential Equations
- • Pattern Recognition
- • Big Data Analytics
- • Numerical Analysis
- • Graph Neural Networks
- • Quantum Computing
- • Cloud Computing
- • Deep Learning & Applications