CUET PG Mathematics 2026
Mathematics
2 Year Masters 5 Years PhD
Duration
Depends on university to university check below in detail
Seats
Preparation Resources
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Syllabus
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πTest Series
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πStudy Notes
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π―Exam Pattern
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π§ͺMock Tests
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β‘Short Notes
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πChapter PYQs
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βοΈChapter Practice
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πFull PYPs
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πΌPlacement
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πCutoff
Expected cutoff marks
Course Overview
The CUET PG Mathematics examination is a national-level entrance test conducted by the National Testing Agency (NTA) for admission to postgraduate Mathematics programs (e.g. M.Sc. Mathematics) across India. It provides a single-window opportunity, replacing multiple university-specific exams, and ensures a transparent admission process. The exam covers core undergraduate mathematics topics, and successful candidates can enroll in top universities like BHU, DU, JNU and others. In summary, CUET PG (Math) is a gateway to premier Math PG courses, standardizing admissions to over 240 participating universities
Eligibility Criteria
A Bachelorβs degree with Mathematics (B.Sc or equivalent) is required. Typically, 50% aggregate for General category and 45% for reserved categories. Some universities may require 45% in Mathematics Honours or 50% aggregate if no honours. There is no age limit. Candidates must also meet specific university criteria (subject prerequisites, etc.) in addition to CUET PG scores.
Course Curriculum
A typical M.Sc. Mathematics curriculum (first year) covers advanced versions of the core topics above β for example, Real Analysis I, Algebra I, Numerical Methods, etc. Electives or second-semester courses may include Topology, Differential Geometry, Complex Dynamics, Probability, or Operations Research. While specific curricula vary by university, the emphasis is on deepening undergraduate concepts into graduate-level theory and applications. (Students should check the specific syllabus of the university they join.)
Career Outcomes
Deep Theoretical Knowledge: Mastery of advanced math subjects (analysis, algebra, etc.).
Analytical & Problem-Solving Skills: Ability to tackle complex quantitative problems.
Research & Logical Thinking: Preparedness for academic research or data-driven roles.
Practical Tools: Familiarity with mathematical software and programming (see below).
Versatility: Qualification for varied careers (teaching, industry, government).
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