MSc Mathematics
Semester-wise Syllabus for MSc Mathematics
Semester 1: Core Foundations
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Advanced Calculus & Real Analysis
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Limits, continuity, sequences, series, Riemann integration
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Metric spaces, uniform convergence
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Abstract Algebra
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Groups, rings, fields, homomorphisms, quotient structures
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Sylow theorems, polynomial rings
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Linear Algebra
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Vector spaces, linear transformations, eigenvalues
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Matrix decompositions (QR, SVD)
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Differential Equations
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ODEs (exact, linear, Bernoulli), PDEs (wave, heat equations)
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Computer Applications in Mathematics
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Programming with Python/Matlab for numerical methods
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Lab/ Practicals
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Solving ODEs/PDEs numerically, coding algorithms
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Semester 2: Advanced Topics
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Complex Analysis
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Analytic functions, Cauchy’s theorem, residue calculus
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Topology
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Basis, compactness, connectedness, quotient topology
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Discrete Mathematics
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Graph theory, combinatorics, Boolean algebra
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Numerical Methods
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Interpolation, numerical integration, root-finding algorithms
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Probability & Statistics
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Distributions, Bayes’ theorem, hypothesis testing
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Lab/ Practicals
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Simulations in MATLAB/R, graph theory applications
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Semester 3: Specializations & Electives
Core Subjects
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Functional Analysis
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Banach and Hilbert spaces, spectral theory
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Number Theory
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Prime numbers, modular arithmetic, cryptography applications
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Electives (Choose 2–3)
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Operations Research: Linear programming, game theory
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Fluid Dynamics: Navier-Stokes equations
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Algebraic Geometry: Varieties, ideals
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Financial Mathematics: Black-Scholes model, stochastic calculus
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Seminar/Project Work
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Research paper review or mini-project (e.g., cryptanalysis, fluid simulation)
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Semester 4: Research & Dissertation
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Thesis/Dissertation
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Original research in pure/applied mathematics (e.g., modeling, proofs)
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Advanced Electives
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Machine Learning Math: Optimization, gradient descent
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Quantum Computing: Linear algebra applications
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Viva Voce
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Defense of dissertation before faculty
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