# B. Tech. in Mathematics and Computing

. The department started a four year B.Tech. program in Mathematics and Computing from Academic year 2019-2020.

. Admission to B.Tech. program in Mathematics and Computing is through JEE (Advanced) 2019-2020.

## Background

Computer science is founded upon Mathematics. Further, computer science is also being used to understanding better and finding solutions to mathematical problems. Graduates of computer science with solid mathematical foundations are currently in great demand and will remain so due to heavy use of computers and computer assisted technologies in our day-to-day life. Keeping this in mind, Mathematics department in collaboration with computer science department is offering a 4-year B. Tech programme in Mathematics and Computing with an emphasis on Artificial Intelligence (AI). This program will give students a formidable combination of Mathematics and Computer Science by concentrating on areas where mathematics and computing are most relevant to each other. The program will prepare graduates well for advanced degrees and careers in a variety of fields in industry. 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 AI. Artificial intelligence is bringing almost revolutionary changes in every field - healthcare, agriculture, security, banking & finance, e-commerce, education, sports, forensics, assistive technologies, etc.There is huge demand for AI talent. According to NITI Aayog report AI has the potential to add USD15.7 trillion to the global GDP by 2030 and roughly USD 1 trillion could be added to India GDP by 2035. The purpose of launching our new course - B.Tech in Mathematics and Computing is to develop a work force which can step up to the challenges of the upcoming age of artificial intelligence and computer assisted technologies where a strong mathematics foundation is required.

## Salient Features of the Program

● The curriculum of this program 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.

● The program core consists of 40% Mathematics, 30% core CS and 30% AI related courses.

● The students will be having flexibility to choose elective courses from a broad spectrum of courses depending on their interests.

● Majority of the courses are designed to give both the theoretical knowledge and practical training through Labs/Practicals/Case studies.

● Option to do projects in other departments/research labs/industries/foreign universities.

● Apart from capstone project, a six months industry internship option is available.

## Career/Job Prospects:

- The data from other IITs where similar programs are running, convey that this is a very successful program and provides a broad spectrum of very good career opportunities. Further, the program is one of the topmost choices with advanced JEE rankers.
- We expect that the graduates from this program will get opportunities in world renowned companies related to information technology, banking & finance, machine learning assisted technologies.
- The graduates could be Data Scientists in different domain.
- We are expecting that program will help the students to bag MS/PhD positions in world renowned universities/Institutes in areas like Machine learning, Artificial Intelligence, Big Data, Mathematical Modeling, Economics and Finance, Image Processing, and many more.
- The advent of Big Data and Data Analytics have created opportunities for Startup Companies with very small partners/employees strength. TBI IIT Ropar supports in house startups.

OR

HS102 English Language Skills (3) [2-2/3-2-13/3-3] instead, for students weak in English

OR

HS102 English Language Skills (3) [2-2/3-2-13/3-3] instead, for students weak in English

OR

Program-Specific General Engineering (3) (viz. “GE106 Materials Science for Electrical and Electronics Engineers” [3-1-0-5-3], for EE)

OR

Program-Specific General Engineering (3) (viz. “GE106 Materials Science for Electrical and Electronics Engineers” [3-1-0-5-3], for EE)

NO102 NSO II (1) [0-0-2-1-1] OR

NS102 NSS II (1) [0-0-2-1-1]

NO102 NSO II (1) [0-0-2-1-1] OR

NS102 NSS II (1) [0-0-2-1-1]

OR

Program Core (3) (for EE)

NSO III (1) [0-0-2-1-1] OR

NSS III (1) [0-0-2-1-1]

OR

EE102 Basic Electronics (3) [2-2/3-2-13/3-3] (for those not having Economics this sem)

GE109 Introduction to Engineering Products (1) [0-0-2-1-1](for those not having Tinkering Lab this sem)

OR

BM101 Biology for Engineers (3) [3-1-0-5-3](for those not having Human Geography and Societal Needs this sem)

NSO IV (1) [0-0-2-1-1] OR

NSS IV (1) [0-0-2-1-1]

OR

HS201 Economics (3) [3-1-0-5-3] (for those who did not have it in 3rd sem)

OR

GE 107 Tinkering Lab (1.5)[0-0-3-3/2-1.5](for those who did not have it in 3rd sem)

OR

Human Geography and Societal Needs (3) [1-1/3-4-11/3-3](for those who did not have it in 4th sem)

OR

Industrial Management (3) [3-1-0-5-3] (for those not having Introduction to Environmental Science & Engineering this sem)

(1) Algebra [3 Credits],

(2) Analysis and Design of Algorithm -[3 Credits],

(3) Foundations of Data Science -[4 Credits]

**Program Core (12) (total 12 credits: 9L max, rest labs) (for those not having Professional Ethics this sem)

OR

*Introduction to Environmental Science & Engineering (3) [3-1-0-5-3] (for those who did not have it in 5th sem)

OR

Program Elective (rest of 6 credits)

(2) Optimization - [3 Credits]

(3) Computing Lab II –[2 Credit]

(4) Elective - [3/4 Credits]

- 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