Online M.Sc. in Maths
Easy EMIAssured job opportunityLimited seats available!
Application Closing soon for Jan 2026 Batch
EMI Starts From: ₹966/-
Live Class:Online
Average Salary:₹1.0LPAEasy EMIAssured job opportunityLimited seats available!Application Closing soon for Jan 2026 BatchEMI Starts From: ₹966/-Live Class:OnlineAverage Salary:₹1.0LPACourse Overview
Kakatiya University’s Online M.Sc. in Mathematics is a 2-year programme designed for graduates seeking advanced mathematical training for academia, analytics and technology roles. The curriculum blends rigorous core theory with applied modules in real analysis, linear algebra, differential equations, complex analysis, topology, numerical methods, probability and optimisation. Delivered by the Centre for Distance and Online Education as a UGC-DEB compliant offering, it combines live interactive sessions, recorded classes and guided self-study—ideal for working professionals. Assessment includes internal assignments and university examinations with opportunities for projects and seminars to ensure practical exposure. Graduates can pursue opportunities in academia, data science foundations, quantitative finance, software testing and research organisations across public, private and social sector organisations.
Course Highlights
- Real & Complex Analysis: Measure, convergence and complex function theory
- Linear Algebra: Vector spaces, eigen theory and linear transformations
- Differential Equations: ODEs/PDEs with qualitative and numerical methods
- Topology: Topological spaces, continuity and compactness
- Probability & Statistics: Random variables, inference and stochastic basics
- Numerical Methods: Approximation, stability and error analysis
- Optimisation: Convexity, KKT conditions and algorithms
- Dissertation: Independent study with presentation and viva
Course
Benefits
Rigorous Foundations Develop proof‑based reasoning and problem‑solving expertise.
Career Flexibility Pathways into teaching, analytics and quantitative roles.
Computational Skills Use tools for numerical and symbolic computation.
Academic Mentoring Guided research seminars and thesis supervision.
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Eligibility
- »Bachelor’s degree (10+2+3) in relevant or allied discipline from a recognised university
- » Open to fresh graduates and working professionals; no age bar
- » Bachelor’s degree with Mathematics major; merit‑based admission per CDOE norms
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Course Syllabus
| S.No | Credit | Subject |
|---|---|---|
| 1 | KUMSM101 | Real Analysis I |
| 2 | KUMSM102 | Linear Algebra I |
| 3 | KUMSM103 | Ordinary Differential Equations |
| 4 | KUMSM104 | Discrete Mathematics |
| 5 | KUMSM105 | Research Methodology |
| S.No | Credit | Subject |
|---|---|---|
| 1 | KUMSM201 | Real Analysis II |
| 2 | KUMSM202 | Complex Analysis |
| 3 | KUMSM203 | Partial Differential Equations |
| 4 | KUMSM204 | Probability Theory |
| 5 | KUMSM205 | Numerical Analysis |
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