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B.Tech in Computation & Mathematics

A 4-year undergraduate programme integrating the precision of mathematics with the power of computation to prepare students for scientific & analytical careers.

B.Tech in computation & mathematics overview

We develop problem-solvers who unite theory and computation to drive real-world innovation, grounded in mathematics, algorithms, and scientific computing for impact across AI, data science, optimisation, and quantitative research. Students experience:

Course grounded firmly

in advanced mathematical disciplines such as linear algebra, complex analysis, enabling conceptual mastery beyond routine engineering maths

Experiential computational

and programming training through data structures, graph algorithms, cryptography and computational biology, all taught alongside mathematical models

Interdisciplinary specialisation

including advanced electives in quantum computing, computational biology, and cryptography enable exploration of frontier scientific domains

Research and innovation

culture through mathematical modelling projects, research internships, and capstone collaborations, to develop analytical creativity and industry-ready expertise

Programme details

Academic structure

Our academic structure is designed to establish robust foundations, followed by increasing specialization in later years.

PIE CHART: CREDIT DISTRIBUTION FOR COMPUTATION & MATHEMATICS

PIE CHART CREDIT DISTRIBUTION FOR COMPUTATION & MATHEMATICS
  • Duration: 4 years / 8 semesters
  • Total credits & degree requirement: The programme requires not less than 165 credits to be awarded a B.Tech degree.
  • Focus areas:
    • Data science/Data analytics
    • Financial mathematics
    • Theoretical computer science/Mathematical sciences
    • Cryptography
    • Quantum computing
CourseL-T-PCredits
Calculus & ODE4-1-05
Chemistry – I2-1-03
Chemistry Lab0-0-21
Introduction to Electrical Engineering/Electronics2-1-24
Engineering Drawing0-0-31.5
Earth and Environmental Sciences2-0-02
Mechanics2-1-03
Media Project1-0-21.5
English3-0-03
Introduction to Entrepreneurship0-0-31
French – I0-2-00.5
Total25.5
Course NameL-T-PCredits
MA1202 – Linear Algebra & complex analyses3-1-04
PH1201 – Physics – I2-1-24
BI1202/CH1204 – Biology (1-7 weeks)/ Chemistry (8-14 weeks)3-0-03 (1.5+1.5)
CS1202 – Discrete Mathematics2-0-02
CS1201 – Introduction to Computing2-1-24
ME1202 – Workshop0-0-21
HS1201 – Entrepreneurship practice0-0-21
HS1202 – Professional Ethics0-1-01
HS1203 – French – II0-2-00.5
Total Credits20.5
Course NameL-T-PCredits
MA2103 – Probability and Statistics3-1-04
PH2102 – Physics-II3-1-25
MA2104 – Real Analysis (Only for CM2021 batch)3-0-03
CS2102 – Data Structures (Common for all B. Tech. 2021 batch)3-0-24
MA2105 – Graph Algorithms (Only for CM2021 batch)3-0-03
MA2106 – Algebra (Only for CM2021 batch)3-0-03
MA2107 – Prog. Workshop (R Programming and GPU computing) (Only for CM2021 batch) (Need a lab ELH-11)0-0-21
HS2101 – Learn start-up (Common to all B. Tech. 2021 batch)0-0-31
HS2102 – Economics (Common to all B. Tech. 2021 batch)3-0-01.5
HS2103 – French-III0-2-00.5
Total Credits26
Course NameL-T-PCredits
MA2208 – Numerical Methods3-0-24
MA2209 – Number theory and Cryptography3-0-03
MA2210 – Optimization Techniques3-0-03
CS2204 – Theory of Computation (Common with CSE 2021 Batch)3-0-03
MA2211 – Computer Organization1-0-01
MA2212 – Functional Analysis3-0-03
MA2213 – Stochastic Process3-0-03
HS2201 – Design Thinking1-0-22
HS2202 – Financial Accounting (7 weeks)3-0-01.5
MA2214 – Programming Workshop (R and MATLAB)0-0-21
HS2203 – French – IV0-2-00.5
Total Credits25
Course NameL-T-PCredits
MA3115 – Computational Methods for PDE3-1-04
CS3102 – Operating Systems (Common with CSE 2021 batch)3-0-24
CS3101 – Design and Analysis of Algorithms (Common with CSE 2021 batch)2-1-24
CS3103 – Database Management Systems (Common with CSE 2021 batch)3-0-24
MA3116 – Financial Mathematics3-0-03
MA3117 – Advanced Linear Algebra3-0-03
MA3118 – Prog. Workshop (Python)0-0-21
HS3101 – French – V0-2-00.5
HSS Elective-I2-0-02
Total Credits25.5
Course NameL-T-PCredits
MA3219 – Mathematical Foundations for Machine Learning3-0-24
CS3203 – Computer Networks (Common with CSE2021 Batch)3-0-24
Elective-I3-0-03
Departmental Elective – Core-Elective – I [choose one elective] Calcus of variationas and integral equations3-0-03
HSS-Elective-II2-0-02
HS3202 – French – VI0-2-00.5
HS3201 – Introduction to Professional Development2-0-02
Project-I0-0-33
Total Credits21.5
Course NameL-T-PCredits
MA 4124 – Quantum Computing3-0-03
MA 4125 – Departmnetal-Elective – II [choose one elective] Dynamical Systems/Computational Topology/Galois Theory]3-0-03
Elective-II3-0-03
Elective-III3-0-03
HSS Elective-III2-0-02
Project-II0-0-44
HS 4101 – French – VII0-2-00.5
Total Credits18.5
Course NameL-T-PCredits
Elective-IV3-0-03
Elective – V3-0-03
Project –III0-0-1212
HS 4201 – French – VIII0-2-00.5
Total Credits18.5

FAQs

The programme is designed to build dual expertise, nurturing students who can think mathematically and code computationally. This rare combination enables them to excel in data science, AI, quantitative finance, research, and advanced analytics roles across industries.

This programme is ideal for curious, analytical thinkers who enjoy logic, problem-solving, and exploring how mathematical theory powers modern technology. It develops both conceptual understanding and practical application, preparing students for innovation-led careers.

While traditional computer science focuses primarily on coding, computation & mathematics deepens students’ understanding of the mathematical principles driving algorithms and models. This gives them a strong conceptual edge in high-end computational research and emerging tech domains.

Students engage in research internships, mathematical modelling workshops, and interdisciplinary capstone projects in collaboration with Mahindra University’s research centres and industry partners, offering real-world exposure from early on.

Graduates are well-prepared for careers in data science, operations research, financial analytics, cybersecurity, AI research, and academia. Many also pursue advanced studies at leading international universities.

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