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B-SC in Mathematics at Shanmugha Arts Science Technology & Research Academy (SASTRA)
Thanjavur, Tamil Nadu
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About the Specialization
What is Mathematics at Shanmugha Arts Science Technology & Research Academy (SASTRA) Thanjavur?
This B.Sc. Mathematics program at Shanmugha Arts, Science, Technology & Research Academy focuses on building a robust foundation in pure and applied mathematics, preparing students for diverse analytical and problem-solving roles. It emphasizes abstract algebraic structures, real analysis, differential equations, and statistical methods, highly relevant for data-driven industries in India. The curriculum integrates modern computational tools and statistical packages, differentiating it in the evolving Indian job market for mathematical sciences.
Who Should Apply?
This program is ideal for fresh graduates with a strong aptitude for logical reasoning and quantitative analysis, aspiring to careers in research, analytics, finance, or teaching. It also suits individuals seeking to pursue higher studies like M.Sc. in Mathematics, Statistics, or Data Science. Students with a 10+2 background in Mathematics and a minimum aggregate of 60% are well-suited, aiming for intellectually stimulating careers in India''''s growing tech and finance sectors.
Why Choose This Course?
Graduates of this program can expect diverse career paths in India as Data Analysts, Actuaries, Financial Modelers, Statisticians, or research assistants. Entry-level salaries typically range from INR 3-6 lakhs per annum, with significant growth potential for experienced professionals. The strong analytical skills acquired are highly valued, aligning with roles in IT, banking, and public sector undertakings. Opportunities also exist for competitive exam preparation and professional certifications like actuarial science.
Student Success Practices
Foundation Stage
Master Fundamental Concepts- (Semester 1-2)
Dedicate consistent effort to thoroughly understand core mathematical concepts in Algebra and Calculus. Regularly solve problems from textbooks and previous year question papers. Focus on logical derivations and proofs, not just memorization, to build a strong analytical base.
Tools & Resources
NCERT textbooks (for revision), Standard reference books (e.g., S. Chand, Arihant), Departmental tutoring sessions, Online platforms like NPTEL for conceptual clarity
Career Connection
A solid foundation is crucial for advanced courses and for excelling in competitive exams (e.g., UPSC, Bank PO, actuarial exams) and quantitative interviews, which are highly valued in India.
Develop Programming and Software Skills- (Semester 1-2)
Actively engage with practical courses like ''''Programming in C'''' and ''''Practical - I/II (Mathematics)''''. Learn to implement mathematical concepts using Python, SciLab/MATLAB, or R. Participate in coding challenges or online courses to sharpen your computational skills.
Tools & Resources
Python, SciLab/MATLAB, R, Online coding platforms (HackerRank, LeetCode), Coursera/Udemy courses on data science basics
Career Connection
Proficiency in computational tools is essential for roles in data analytics, scientific computing, and finance, making you highly employable in India''''s technology-driven job market.
Cultivate Effective Study Habits- (Semester 1-2)
Form study groups with peers to discuss challenging topics, teach each other concepts, and collaborate on problem-solving. Practice active recall and spaced repetition for better retention. Regularly attend lectures and clarify doubts promptly with faculty members.
Tools & Resources
Peer study groups, Flashcard apps (Anki), Lecture notes and course materials, Faculty office hours
Career Connection
Strong academic performance and collaborative skills enhance your CV, improve chances for internships, and prepare you for team-based projects common in Indian industries and research institutions.
Intermediate Stage
Pursue Internships and Mini-Projects- (Semester 3-5)
Seek out internships during summer breaks or work on mini-projects that apply mathematical theories to real-world problems. Focus on areas like data analysis, financial modeling, or scientific research. Leverage university career services and faculty networks for opportunities.
Tools & Resources
University placement cell, LinkedIn, Internshala, Guidance from project supervisors, Datasets from Kaggle for practice
Career Connection
Practical experience gained through internships is highly valued by Indian employers, providing hands-on skills and professional networking opportunities critical for placements.
Specialize through Electives and Advanced Learning- (Semester 3-5)
Carefully choose Discipline Specific Electives (DSEs) based on your career interests, whether it is pure mathematics (e.g., Graph Theory), statistics (e.g., Mathematical Statistics II), or applied areas (e.g., Machine Learning). Supplement your learning with advanced online courses or workshops.
Tools & Resources
NPTEL courses on advanced topics, Specialized books and journals, Workshops and seminars conducted by departments, Udemy/Coursera for niche skills
Career Connection
Specialized knowledge makes you a strong candidate for specific roles in analytics, finance, or IT sectors in India, demonstrating focused expertise beyond general mathematics.
Participate in Competitions and Olympiads- (Semester 3-5)
Engage in national and international mathematics competitions, coding challenges, or data science hackathons. These platforms test problem-solving abilities under pressure and provide exposure to diverse mathematical applications. Focus on improving logical reasoning and analytical speed.
Tools & Resources
Indian Mathematical Olympiad (IMO), Putnam Competition (if applicable), Kaggle competitions, CodeChef, HackerEarth
Career Connection
Winning or even participating in such competitions significantly boosts your resume, showcasing your problem-solving prowess, and can catch the eye of top recruiters in India.
Advanced Stage
Focus on Project-Based Learning and Research- (Semester 5-6)
For Project I and II, select topics that align with your career aspirations and involve significant application of mathematical concepts. Aim to publish your findings in reputed conferences or journals, even at an undergraduate level. Collaborate with faculty on ongoing research.
Tools & Resources
Research papers and academic databases, Statistical software (R, Python, SAS), Thesis writing guides, Faculty mentors
Career Connection
High-quality project work and potential publications are invaluable for postgraduate admissions (M.Sc./Ph.D.) in top Indian and international universities, and for research-oriented roles.
Intensive Placement and Higher Studies Preparation- (Semester 5-6)
Actively prepare for campus placements by honing interview skills, mock interviews, and technical aptitude tests. If pursuing higher studies, prepare for entrance exams like GATE, JAM, or GRE. Attend workshops on resume building and LinkedIn profile optimization.
Tools & Resources
Placement cell workshops, Online aptitude test platforms, Interview preparation books (e.g., R.S. Aggarwal), GRE/GATE coaching materials
Career Connection
Diligent preparation ensures you are job-ready for leading companies in India or well-equipped for entrance to prestigious postgraduate programs, securing your future career trajectory.
Network and Seek Mentorship- (Semester 5-6)
Actively network with alumni, industry professionals, and faculty members. Attend industry seminars, guest lectures, and career fairs to explore opportunities and gain insights. Seek mentorship from experienced individuals in your target career field.
Tools & Resources
LinkedIn, Alumni association events, Industry conferences (e.g., analytics summits), Faculty advisors and industry experts
Career Connection
Networking opens doors to hidden job opportunities, valuable career advice, and potential referrals, which are crucial for navigating the competitive Indian job market.
Program Structure and Curriculum
Eligibility:
- A pass in the Higher Secondary Examination (10+2) or an equivalent examination, with Mathematics as one of the subjects and a minimum aggregate of 60% marks in the qualifying examination.
Duration: 6 semesters / 3 years
Credits: 140 Credits
Assessment: Internal: 40%, External: 60%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 101 | Algebra - I | Core | 4 | Vector Spaces, Linear Transformations, Matrices and Eigenvalues, Inner Product Spaces, Diagonalization and Bilinear Forms |
| MAA 102 | Calculus - I | Core | 4 | Functions of one Variable, Limits and Continuity, Derivatives and Applications, Integrals and Applications, Sequences and Series |
| CSA 101 | Fundamentals of Computer | Allied | 3 | Introduction to Computers, Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Introduction to Internet |
| LAA 101 | Communicative English | Language | 3 | Introduction to Communication, Listening Skills, Speaking Skills, Reading Skills, Writing Skills |
| EAA 101 | Environmental Studies | Ability Enhancement Compulsory Course | 2 | Introduction to Environmental Studies, Natural Resources, Ecosystems, Biodiversity and Conservation, Environmental Pollution |
| MAP 101 | Practical - I (Mathematics) | Practical | 2 | Python Programming Basics, Data Types and Operators, Control Structures, Functions and Modules, Numerical Computations |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 103 | Algebra - II | Core | 4 | Group Theory, Subgroups and Cosets, Rings and Fields, Integral Domains, Polynomial Rings |
| MAA 104 | Calculus - II | Core | 4 | Functions of Several Variables, Partial Derivatives, Multiple Integrals, Vector Calculus, Ordinary Differential Equations |
| CSA 102 | Programming in C | Allied | 3 | Introduction to C Programming, Control Statements, Arrays and Strings, Functions and Pointers, Structures and File Handling |
| LAA 102 | Academic Writing | Language | 3 | Basics of Academic Writing, Paragraph and Essay Writing, Report Writing, Research Paper Structure, Referencing and Citation |
| GBA 101 | Personality Development | Skill Enhancement Course | 2 | Self-Awareness and Self-Esteem, Communication Skills, Interpersonal Skills, Leadership and Teamwork, Time Management and Goal Setting |
| MAP 102 | Practical - II (Mathematics) | Practical | 2 | SciLab/MATLAB Environment, Matrix Operations, Plotting Functions, Solving Equations, Numerical Methods Applications |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 201 | Real Analysis - I | Core | 4 | Real Number System, Sequences and Series, Continuity and Uniform Continuity, Differentiation, Riemann Integration |
| MAA 202 | Differential Equations - I | Core | 4 | First Order Ordinary Differential Equations, Linear Differential Equations of Higher Order, Series Solutions of ODEs, Laplace Transforms, Systems of Linear Differential Equations |
| ELA 201 | Object-Oriented Programming with C++ | Allied (DSE from another department) | 3 | Principles of OOP, Classes and Objects, Inheritance, Polymorphism and Virtual Functions, File Handling and Exception Handling |
| GBA 201 | Professional Ethics and Values | Skill Enhancement Course | 2 | Introduction to Ethics, Professional Ethics, Ethical Theories, Values and Morals, Contemporary Ethical Issues |
| MAA 203 | Mathematical Statistics - I | Core | 4 | Probability Theory, Random Variables and Distributions, Mathematical Expectation, Moment Generating Functions, Special Discrete and Continuous Distributions |
| MAP 201 | Practical - III (Mathematics) | Practical | 2 | Statistical Software Basics (R/Python), Descriptive Statistics, Probability Distributions Simulation, Data Visualization, Introduction to Hypothesis Testing |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 204 | Real Analysis - II | Core | 4 | Functions of Bounded Variation, Riemann-Stieltjes Integral, Measure Theory, Lebesgue Measure, Lebesgue Integration |
| MAA 205 | Differential Equations - II | Core | 4 | Introduction to Partial Differential Equations, First Order PDEs, Second Order PDEs, Classification of PDEs, Boundary Value Problems |
| ELA 202 | Database Management Systems | Allied (DSE from another department) | 3 | Introduction to DBMS, Relational Model, SQL Queries and Operations, Database Normalization, Transaction Management and Concurrency Control |
| LAA 201 | Quantitative Aptitude | Skill Enhancement Course | 2 | Number Systems and HCF/LCM, Percentages, Profit and Loss, Time and Work, Speed and Distance, Ratio, Proportion and Averages, Data Interpretation |
| MAA 206 | Mathematical Statistics - II | Core | 4 | Sampling Distributions, Point Estimation, Interval Estimation, Hypothesis Testing, Analysis of Variance |
| MAP 202 | Practical - IV (Mathematics) | Practical | 2 | Advanced Statistical Software (R/Python), Hypothesis Testing Implementation, Regression and Correlation Analysis, ANOVA Techniques, Time Series Analysis Introduction |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 301 | Complex Analysis | Core | 4 | Complex Number System, Analytic Functions, Conformal Mappings, Complex Integration, Residue Theory and Applications |
| MAA 302 | Numerical Analysis | Core | 4 | Solution of Algebraic and Transcendental Equations, Interpolation and Approximation, Numerical Differentiation, Numerical Integration, Numerical Solution of Ordinary Differential Equations |
| MAA 303 | Linear Programming | Core | 4 | Formulation of LPP, Graphical Method, Simplex Method, Duality Theory, Transportation and Assignment Problems |
| MAD 301 | Discrete Mathematics | Discipline Specific Elective | 4 | Mathematical Logic and Proofs, Set Theory and Relations, Functions and Induction, Combinatorics and Counting, Algebraic Structures |
| MAD 304 | Graph Theory | Discipline Specific Elective | 4 | Introduction to Graphs, Paths, Cycles and Trees, Connectivity and Separability, Planar Graphs, Coloring and Matching |
| GEC XXX | General Elective Course - I | General Elective | 2 | |
| MAP 301 | Project - I (Mathematics) | Project | 2 | Literature Survey, Problem Formulation and Scope, Methodology Development, Data Collection and Analysis, Preliminary Report Writing |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MAA 304 | Functional Analysis | Core | 4 | Metric Spaces, Normed Linear Spaces, Banach Spaces, Hilbert Spaces, Linear Operators and Functionals |
| MAA 305 | Mathematical Modeling | Core | 4 | Introduction to Modeling, Continuous and Discrete Models, Population Dynamics, Epidemic Models, Optimization and Simulation Models |
| MAA 306 | Operation Research | Core | 4 | Network Analysis, Queuing Theory, Inventory Control Models, Game Theory, Dynamic Programming |
| MAD 307 | Cryptography | Discipline Specific Elective | 4 | Classical Cryptographic Techniques, Symmetric Key Cryptography (DES, AES), Asymmetric Key Cryptography (RSA), Hash Functions and Digital Signatures, Key Management and Security Protocols |
| MAD 310 | Machine Learning | Discipline Specific Elective | 4 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Neural Networks and Deep Learning Basics, Model Evaluation and Hyperparameter Tuning |
| GEC XXX | General Elective Course - II | General Elective | 2 | |
| MAP 302 | Project - II (Mathematics) | Project | 2 | Advanced Research and Development, Data Analysis and Model Implementation, Results Interpretation and Discussion, Thesis Writing and Documentation, Viva Voce and Presentation |
