H a l t o n A c a d e m y

About Us

Our goal is simple: we help you grow to be your best. Whether you’re a student, working professional, corporate organization or institution, we have tailored initiatives backed by industry specific expertise to meet your unique needs.

Contact Info

Halton Academy For Management and Technology Private Limited,
39/2475-B1 LR Towers, South Janatha Road, Palarivattom, Ernakulam, Kerala - 682025, India.

+91-7511-1890-01

4 Francis Street, le2 2bd, England,
United Kingdom.

hello@haltonacademy.com

MSc Mathematics

Semester-wise Syllabus for MSc Mathematics

 

Semester 1: Core Foundations

  1. Advanced Calculus & Real Analysis

    • Limits, continuity, sequences, series, Riemann integration

    • Metric spaces, uniform convergence

  2. Abstract Algebra

    • Groups, rings, fields, homomorphisms, quotient structures

    • Sylow theorems, polynomial rings

  3. Linear Algebra

    • Vector spaces, linear transformations, eigenvalues

    • Matrix decompositions (QR, SVD)

  4. Differential Equations

    • ODEs (exact, linear, Bernoulli), PDEs (wave, heat equations)

  5. Computer Applications in Mathematics

    • Programming with Python/Matlab for numerical methods

  6. Lab/ Practicals

    • Solving ODEs/PDEs numerically, coding algorithms


Semester 2: Advanced Topics

  1. Complex Analysis

    • Analytic functions, Cauchy’s theorem, residue calculus

  2. Topology

    • Basis, compactness, connectedness, quotient topology

  3. Discrete Mathematics

    • Graph theory, combinatorics, Boolean algebra

  4. Numerical Methods

    • Interpolation, numerical integration, root-finding algorithms

  5. Probability & Statistics

    • Distributions, Bayes’ theorem, hypothesis testing

  6. Lab/ Practicals

    • Simulations in MATLAB/R, graph theory applications


Semester 3: Specializations & Electives

Core Subjects

  1. Functional Analysis

    • Banach and Hilbert spaces, spectral theory

  2. Number Theory

    • Prime numbers, modular arithmetic, cryptography applications

Electives (Choose 2–3)

  • Operations Research: Linear programming, game theory

  • Fluid Dynamics: Navier-Stokes equations

  • Algebraic Geometry: Varieties, ideals

  • Financial Mathematics: Black-Scholes model, stochastic calculus

  1. Seminar/Project Work

    • Research paper review or mini-project (e.g., cryptanalysis, fluid simulation)


Semester 4: Research & Dissertation

  1. Thesis/Dissertation

    • Original research in pure/applied mathematics (e.g., modeling, proofs)

  2. Advanced Electives

    • Machine Learning Math: Optimization, gradient descent

    • Quantum Computing: Linear algebra applications

  3. Viva Voce

    • Defense of dissertation before faculty