Mathematical and Computational Sciences

The Mathematical and Computational Sciences Major offers students a rigorous foundation in the fundamentals of Mathematics and Computational Sciences, including Data Sciences. It also prepares them to solve complex interdisciplinary problems by applying mathematical and computational tools. The Major offers a unique blend of courses in theory and modern applications of Mathematics and Computational Sciences. The objective is to create graduates with a deep understanding of the fundamental principles of mathematics who can apply strong computational techniques to model and solve problems in Physics, Economics, Finance, Engineering, and other domains.

Highlights of the Mathematical and Computational Sciences Major:

Rigorous Foundation: The Major provides a rigorous foundation in Mathematics and Computational Sciences through carefully designed courses.
Flexibility: The Major offers students a wide range of elective courses from the following areas:
- Pure Mathematics
- Data Sciences and Machine Learning
- Mathematical Biology
- Mathematics in Engineering
- Quantum Computing
- Mathematical Economics
- Mathematical Finance
Interdisciplinary Problem Solving: Most real-life problems are complex and often require an interdisciplinary approach. The Major offers students electives from exciting interdisciplinary fields such as Bio-Computing, Data Sciences, Quantum Computing, and more.
Undergraduate Research: The faculty at the Mathematical and Physical Sciences division are actively engaged in research, providing students with opportunities to work on research projects under their direct supervision.
Employable Skills: The Major is designed to teach students valuable and functional employability skills needed for a career in industry and academia. The critical thinking and problem-solving skills and the breadth in curricula offered at Ahmedabad University will impart a rigorous and broad-based education in mathematics and computational sciences helpful in many practical professions.

Learning Objectives

The Mathematical and Computational Sciences Major seeks to provide students with the following:

A rigorous foundation in fundamentals of Mathematics and Computational Sciences
Skills to pursue rewarding careers in Mathematics, Computing, and Data Sciences in industry, and higher studies
The ability to solve complex real-world problems by applying problem-solving skills and the knowledge gained from a broad education in Mathematics, Computing, Data Sciences, Humanities, Social Sciences, and other Physical and Biological Sciences
The ability to engage in research in Mathematics and Computer Science-related fields
Critical thinking and logical reasoning skills needed to understand abstract mathematical concepts and proofs
The ability to effectively communicate mathematical ideas and concepts

Learning Outcomes

Successful completion of the Bachelor of Science (Honours) Programme with a Mathematical and Computational Sciences Major will enable the student to:

Demonstrate a firm understanding of the basic principles of Mathematics and Computational Sciences
Understand mathematical arguments and proofs
Write and communicate mathematical proofs
Analyse and interpret real-world data in a given context using statistical tools
Identify and use relevant programming languages and computational tools to solve real-world problems
Create mathematical models and explain a wide range of real-world phenomenon
Apply the knowledge of Mathematics, Statistics, Data Sciences, and Computational tools to solve complex multi-disciplinary problems

To learn more about the Mathematical and Computational Sciences (MCS) programme at Ahmedabad University you may send an email to [email protected].

Major Must Knows

Offered by	School of Arts and Sciences
Programme	Bachelor of Science (Honours)
Degree	Bachelor of Science (Honours)
Minimum Programme Credits	120*
Minimum Major Credits	60*

Curriculum Structure (Bachelor of Science (Honours) Programme)

I Foundation Programme

12 Credits

All students entering the undergraduate programme complete our common core, The Foundation Programme, in the first year. The Foundation Programme is designed around four Studios, each of three credits. They are:

Democracy and Justice
Environment and Climate Change
Neighbourhoods
Water

The studios deliver interdisciplinary learning around six domains:
Data Science, Communication, Behaviour, Constitution & Civilisation, Materials, and Biology & Life.

II General Education Requirement

30 Credits

Humanities and Languages GER

Social Sciences GER

Biological and Life Sciences GER

Mathematical and Physical Sciences GER

Performance and Visual Arts GER

GER Elective 1: Communication- I

GER Elective 2: Communication- II

GER Elective 3: Data Science

GER Elective 4: Any course at the university outside the major

GER Elective 5: Any course at the university outside the major

III Major Requirements

60 Credits

Major Requirements	Credits
Major Core	36
Probability Mathematical Statistics Discrete Mathematics Design and Analysis of Data structures and Algorithms Applied Linear Algebra /Advanced Linear Algebra Differential Equations Multivariable Calculus Introduction to Real Analysis Machine Learning Artificial intelligence (AI) Mathematical Modelling Introduction to Abstract Algebra
Undergraduate Thesis	6
*Major Electives*	18
Pure Mathematics Complex Analysis Introduction to Differential Geometry Introduction to Combinatorics Number Theory Introduction to Topology Introduction to Algebraic Topology Introduction to Measure Theory Introduction to Functional Analysis Introduction to Representation Theory Introduction to Commutative Algebra Applied Mathematics / Computational Sciences Calculus of Variations Graph Theory Introduction to Numerical Analysis Introduction to Partial Differential Equations Mathematical Optimization and Linear Programming Mathematical Modelling of Climate Change Mathematical Ecology Introduction to Fourier Analysis and Its Applications Mathematical Statistics Stochastic Process Python Programming Theory of Computation Statistical Learning Theory Nonlinear Dynamics Mathematical Biology Quantum Mechanics-I Social Network Analysis (SNA) Introduction to Quantum Computing Game Theory and its Applications –I Financial Modelling Financial Econometrics Introduction to Fintech Basic Bioinformatics Computational Structural Biology Natural Language Processing Computer Vision Wireless Communications Information and Coding Theory Data Analytics and Visualisation Big Data Analytics Introduction to Quantum Machine Learning

IV Free Electives

18 Credits

Free Electives provide flexibility to students to customise their education at the University.

Free Electives allow you to take additional courses as per your choice (apart from the Foundation Programme, GERs and Major Requirements), across the university to increase your depth or breadth.

A student can take a Minor in any area designated as a Minor at any School or Centre of the University. Some Minors may have specific pre-requisites. Free Electives can also be used along with some courses from the Major Requirements and GERs towards a Minor.

V Volunteerism

Required

All students will complete 30 hours of engagement with society to develop a sense of engagement, concern, build problem solving skills, and understand the role of an engaged member of a society. This will be done through a mandatory course, Engagement with Society, that would be a graduation requirement. This course can be taken anytime during the stay at the University but it is advised that the student engage with the courses during the first two years at the University. The 30 hours of volunteer work may be completed during one semester or during the Winter or Summer Break.

*The curriculum structure and number of credits are under review and are likely to increase.