Chennai Mathematical Institute
Course Details


BS (Honours) | MSc Mathematics | MSc Computer Science | MSc Data Science

BS (Honours)

The aim of the BS (Honours) Programmes is to train talented students for academic and professional careers requiring exceptional skills in mathematics, computer science and physics.

The BS (Honours) Programme is a 4-year course. All BS (Honours) students undergo the same core set of basic and advanced undergraduate courses in mathematics in the first two years. After the second year, students have to choose a focus subject among mathematics, computer science and physics. Depending on the choice of subject, the degree awarded is BS (Honours) Mathematics or BS (Honours) Mathematics and Computer Science or BS (Honours) Mathematics and Physics.

Regular full semester courses at CMI carry 4 credits. Some elective courses run for shorter periods and carry 2 credits or 1 credit. A student must complete a minimum of 144 credits (36 regular courses) to earn a BS (Honours) degree. A student can exit with a BSc degree after three years on completing 112 credits (28 regular courses).

Course Details


Semester I

The first semester is common to all BS students, and consists of the following courses.

Semester I
 
  • Algebra I
  • Analysis I
  • Humanities I (English)
  • Introduction to Programming
  • Classical Mechanics I

Semesters II–IV

After the first semester, students must make a choice between Computer Science and Physics as a second subject. This choice is entirely left to the student. There are no constraints based on academic performance or on the number of students opting for the two subjects.

Students who opt for Computer Science have the following core requirements in Semesters II–IV.

Semester IISemester IIISemester IV
 
  • Algebra II
  • Calculus I
  • Probability Theory
  • Advanced Programming
  • Discrete Mathematics
  • Algebra III
  • Analysis II
  • Calculus II
  • Design and Analysis of Algorithms
  • Theory of Computation
  • Complex Analysis
  • Differential Equations
  • Topology
  • Programming Language Concepts

Students who opt for Physics have the following core requirements in Semesters II–IV.

Semester IISemester IIISemester IV
 
  • Algebra II
  • Calculus I
  • Probability Theory
  • Classical Mechanics II
  • Electrodynamics I
  • Algebra III
  • Analysis II
  • Calculus II
  • Quantum Mechanics I
  • Thermal Physics
  • Physics Lab I
  • Complex Analysis
  • Differential Equations
  • Topology
  • Optics
  • Quantum Mechanics II
  • Physics Lab II

All students must complete a compulsory one semester non-credit course in Environmental Science.

Semesters V–VIII

To graduate with a BS (Honours) degree after 4 years, students must choose one of the following subjects as a specialization after Semester IV.

  • Mathematics
  • Computer Science
  • Physics

Depending on the specialization, they have to complete a depth requirement of 32 credits in that subject. The depth requirements are summarized below. The remaining credits can be electives chosen from any subject area, subject to a minimum of 8 credits in Humanities.

Mathematics

  • Compulsory courses (12 credits): Graduate Algebra I, Graduate Analysis I, Introduction to Manifolds
  • 2 courses (8 credits) from: Graduate Algebra II; Graduate Analysis II; Graduate Topology II
  • 3 courses (12 credits) from list of Mathematics electives

Students who specialize in Mathematics in Semesters V–VIII will be awarded a BS (Honours) in Mathematics, with a minor in Computer Science or Physics, depending on the subject chosen after Semester I.

Computer Science (This option is available only to students who chose Computer Science after Semester I.)

  • Compulsory courses (16 credits): Introduction to Logic, Complexity Theory I, Networks \emph{or} Databases, Theoretical Foundations of Machine Learning \emph{or} Data Mining and Machine Learning
  • Electives (16 credits): Grouped in baskets --- Algorithms and Complexity, Logic and Automata, Information theory and Coding, Distributed Computing, Machine Learning, Systems. No more than 8 credits can be taken from any one basket.

Students who specialize in Computer Science in Semesters V–VIII will be awarded a BS (Honours) in Mathematics and Computer Science.

Physics (This option is available only to students who chose Physics after Semester I.)

  • Compulsory courses (16 credits): Statistical Physics Computational Physics, Quantum Mechanics 3, Relativity
  • Electives (16 credits) from Quantum Field Theory, Nonlinear Dynamics and Chaos, Astrophysics, Gravitational Waves, Mathematical Physics, Fluid / Continuum Mechanics, Condensed Matter Physics, Quantum Information and Computation; Advanced Lab

Students who specialize in Physics in Semesters V–VIII will be awarded a BS (Honours) in Mathematics and Physics.

For students who specialize in Computer Science and Physics, there is a possibility of completing 16 credits through a thesis, subject to approval.

Minor in Data Science

Students of any of the three BS (Honours) programmes can additionally qualify for a minor in Data Science by completing the following 5 courses, worth 20 credits.

  • Probability and Statistics with R
  • Linear Algebra and its Applications
  • Data Mining and Machine Learning
  • Regression and Classification
  • Advanced Machine Learning

3 year exit option

Students can exit with BSc after 3 years, by completing 112 credits including one elective course in Humanities. Students who opted for Computer Science after Semester I will graduate with a BSc in Mathematics and Computer Science. Students who opted for Physics after Semester I will graduate with a BSc in Mathematics and Physics.

Note: Small variations may be incorporated in this schedule, as recommended by the Academic Council.

MSc Mathematics

The aim of the MSc Programme in Mathematics is to introduce students to advanced topics in mathematics and lay a firm foundation for pursuing further research while also enabling students to acquire advanced skills that will enhance their effectiveness in professional careers.

The MSc Programme in Mathematics is a two-year course. Regular full semester courses at CMI carry 4 credits. A student must complete a minimum of 64 credits (16 regular courses) to earn an MSc degree in Mathematics. Some elective courses run for shorter periods and carry 2 credits or 1 credit. These may be accumulated to make up the credit requirement under Electives. Part of the course-work for the MSc Mathematics programme is concurrent with the PhD Mathematics programme.

Course Details Click here for the syllabus of the core courses.

Semester ISemester II
First year
  • Graduate Algebra I
  • Graduate Analysis I
  • Graduate Topology I
  • Introduction to Manifolds
  • Graduate Algebra II
  • Graduate Analysis II
  • Graduate Topology II
  • Complex Analysis
Semester IIISemester IV
Second year
  • Directed Reading
  • Elective I
  • Elective II
  • Elective III
  • MSc Thesis
  • Elective IV
  • Elective V
Electives Note: Small variations may be incorporated in this schedule, as recommended by the Academic Council.

MSc Computer Science

The aim of the MSc Programme in Computer Science is to introduce students to advanced topics in computing and lay a firm foundation for pursuing further research while also enabling students to acquire advanced skills that will enhance their effectiveness in professional careers.

The MSc Programme in Computer Science is a two-year course. Regular full semester courses at CMI carry 4 credits. A student must complete a minimum of 64 credits (16 regular courses) to earn an MSc degree in Computer Science. Some elective courses run for shorter periods and carry 2 credits or 1 credit. These may be accumulated to make up the credit requirement under Electives.

Course Details

Core courses

There are four core courses in the programme.

  • Mathematical Toolkit I
  • Design and Analysis of Algorithms
  • Theory of Computation
  • Mathematical Logic

At the discretion of the Board of Studies, a student who has already completed any of the core courses as an undergraduate may substitute these courses by a suitable number of alternative courses to make up the overall course requirements.

Electives

The electives that have been offered at CMI in recent years include:

  • Approximation Algorithms
  • Automata Theory and Verification,
  • Coding Theory
  • Complexity Theory
  • Computational Geometry
  • Concurrent Programming
  • Cryptography and Security
  • Data Mining and Machine Learning
  • Digital Systems Design and Modelling
  • Discrete Mathematics
  • Finite Model Theory
  • Logic, Automata and Games
  • Logical Foundations of Databases
  • Model Checking and Systems Verification
  • Optimization
  • Probability and Statistics
  • Program Analysis
  • Quantitative Automata Theory
  • Randomized Algorithms
  • Theorem Proving

The exact list of elective courses being offered will be announced at the beginning of each semester.

Project/Dissertation

The project/dissertation carries 16 credits (the equivalent of four regular courses).

Note: Small variations may be incorporated in this schedule, as recommended by the Academic Council.

MSc Data Science

The aim of the MSc Programme in Data Science is to equip students with the relevant background from mathematics, statistics and computing required for data science, followed by basic and advanced course in analytics, machine learning and other related topics. The programme enables students to acquire advanced skills that will enhance their effectiveness in professional careers, while also laying a firm foundation for pursuing further research.

The MSc Programme in Data Science is a two-year course. Regular full semester courses at CMI carry 4 credits. A student must complete a minimum of 64 credits (16 regular courses) to earn an MSc degree in Data Science. Some elective courses run for shorter periods and carry 2 credits or 1 credit. These may be accumulated to make up the credit requirement under Electives.

Course Details

Semester I
 
  • Mathematical Methods – Analysis
  • Probability and Statistics with R
  • Programming and Data Structures with Python
  • Visualization (2 credits)
  • RDBMS and SQL (2 credits)
Semester II
 
  • Linear Algebra and its Applications
  • Data Mining and Machine Learning
  • Algorithms
  • Distributed Computing and Big Data
Summer Internship (compulsory)
 
Semester III
 
  • Regression and Classification
  • Advanced Machine Learning
  • Elective 1
  • Elective 2
Semester IV
 
  • Elective 3
  • Elective 4
  • Elective 5
  • Elective 6
Elective Courses
 
  • Advanced Regression and Classification
  • Algorithmic Trading
  • Algorithms for Big Data
  • Bayesian Data Analysis
  • Economics
  • Finance
  • Financial Data Analysis
  • Industry Project
  • Mathematical Modeling
  • Optimization
  • Risk Management
  • Text Analytics
Note: Small variations may be incorporated in this schedule, as recommended by the Academic Council.