M.Sc. in Applied Mathematics and Computing

Know More About M.Sc. in Applied Mathematics and Computing

Course Offered Duration (in Years) Eligibility
M.Sc. in Applied Mathematics & Computing 2

Graduate with Maths / Statistics / BCA / B.Sc.CS / B.Sc. IT / B.Sc.- Data Science and having minimum 55% marks from a recognized University / Institution.

A Personal Interview will be conducted by the Competent Authority of the University

Disclaimer: TNU reserves the right for relaxation in admission criteria for the most deserving candidates.

M.Sc. Applied Mathematics and Computing programme is design with an outright emphasis on mathematics, numerical methods and scientific computation covering theoretical, computational and practical aspects to resolve various problems that arise in industry and business, with an emphasis on developing computable solutions. The core mathematics courses is aimed at building a strong foundation in the subject, the laboratory-based subjects give the exposure and training in application-oriented practical subjects specially on computing. Internships programs at various IITs and NITs, IT and Banking Sectors is part of the curriculum. Faculty members are experienced in both Academic and Industry. Industrial experts visit the campus, to train students in research and industrial opportunities.

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Expert Committee

LABORATORY

Computer and Engineering lab consists of software like Kali Linus, VMWare, Open IAM, Vulnerability scanners, NsLookUP, R, Oracle , Hadoop, Sikuli are provided

Career Prospects

M.Sc. in Applied Mathematics and Computing program, in particular, the physical applied areas and the theory and implementation of numerical methods and algorithms have wide-ranging applications in both the public and private sectors. This program shall prepare Students for Careers in Data Science. Thus, the subject of Computational Mathematics has become

increasingly prominent. Postgraduates in Applied Mathematics and Computing can work in a multitude of challenged and rapidly adapting industries of science and technology, finance and banking to businesses and health care. Skills like problem solving, decision-making, and critical thinking are highly preferable for a candidate in the present era. The Course can lead to two distinct career directions: academia or industry. There is always an opportunity for teaching and research jobs along with a wide range of scope in various industry-related jobs in statistics, engineering, physical science, computer science, financial journalism, banking, insurance, and economics. Postgraduates can acquire various job opportunities as a Meteorologist, Data Scientist, Research Scientist, Cloud Computing Architect, Software Developer, Actuarial Analyst, Data Analyst, Financial Analyst, and so on. Postgraduates may pursue a Ph.D. program, which will help to get more knowledge, experience, and higher job roles.

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Our Faculty

Course Structure

  • Semester 1
  • Semester 2
  • Semester 3
  • Semester 4

Semester 1

Sl. No

Course Title

Hours per Week

Credit Units

Lecture

Tutorial

Practical

1

Discrete Mathematics

3

1

0

4

2

Modern Algebra

3

1

0

4

3

Linear Algebra

3

1

0

4

4

Real Analysis

3

1

0

4

5

Computer Programming

3

0

3

6

 

Number of Hours

15

4

3

 

Total Number of Hours: 22

Total Credits

22

Semester 2

Sl. No

Course Title

Hours per Week

Credit Units

Lecture

Tutorial

Practical

1

Data Structures and Design of Algorithms

3

1

2

6

2

Object Oriented Programming

3

0

3

6

3

Probability & Statistics

3

1

1

5

4

Differential Equations

3

1

0

4

5

Complex Analysis

3

1

0

4

 

Number of Hours

15

4

6

 

Total Number of Hours: 25

Total Credits

25

*Students are required to attend MOOCs Course of ‘Introduction to Python’ during semester recess after IInd Semester

Semester 3

Sl. No

Course Title

Hours per Week

Credit Units

Lecture

Tutorial

Practical

1

Fundamentals of Operating System and Networking

3

1

2

6

2

Theory of Computation

3

1

0

4

3

Statistical Inference

3

1

1

5

4

Elective-I*

4

5

Elective-II*

4

6

Seminar on Project

0

0

3

3

 

Number of Hours

     

 

Total Number of Hours: 26

Total Credits

26

 

*Students are required to attend MOOCs Course of ‘Software Engineering’ during semester recess after IIIrd Semester

*List of Electives for Elective-I: (Choose any of the Courses)

 

Sl. No.

Course Name

L

T

P

1.

Financial Mathematics

2

1

1

2.

Optimization Techniques

3

0

1

3.

Computational Fluid Dynamics

2

0

2

4.

Theory of Elastic Waves

4

0

0

 

*List of Electives for Elective-II: (Choose any of the Courses)

 

Sl. No.

Course Name

L

T

P

1.

Introduction to Artificial Intelligence & Machine Learning

3

0

1

2.

Introduction to Actuarial Science

3

0

1

3.

Introduction to Cyber Security & Block Chain

3

0

1

4.

Soft Computing

3

0

1

5.

Information and Coding Theory

3

0

1

Semester 4

Sl. No

Course Title

Hours per Week

Credit Units

Lecture

Tutorial

Practical

1

Database Management System

3

1

2

6

2

Numerical Linear Algebra

3

0

2

5

3

Advanced Numerical Analysis

3

0

2

5

4

Elective-III*

4

5

Elective-IV*

4

6

Project (Dissertation & Seminar)

0

0

12

12

 

Number of Hours

     

 

Total Number of Hours: 36

Total Credits

36

 

*List of Electives for Elective-III: (Choose any of the Courses)

 

Sl. No.

Course Name

L

T

P

1.

Mathematical Modelling and Simulation

4

0

0

2.

Integral Transformations

4

0

0

3.

Stochastic Processes

3

1

0

4.

Time Series Analysis

4

0

0

 

*List of Electives for Elective-IV: (Choose any of the Courses)

 

Sl. No.

Course Name

L

T

P

1.

Cloud Computing

2

0

2

2.

Graph Theory

3

1

0

3.

Compiler Construction

3

0

1

4.

Parallel Processing

3

1

0

5.

Quantum Computing

4

0

0

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