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B-SC in Mathematics at Marwadi University
Rajkot, Gujarat
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About the Specialization
What is Mathematics at Marwadi University Rajkot?
This B.Sc. Mathematics program at Marwadi University focuses on providing a strong foundation in pure and applied mathematics. It covers core areas like algebra, calculus, real and complex analysis, alongside modern applications such as mathematical modeling, numerical methods, and data science tools. The program aims to equip students with analytical and problem-solving skills crucial for diverse fields in the Indian industry.
Who Should Apply?
This program is ideal for high school graduates with a strong aptitude for logical reasoning and quantitative analysis, typically those who have studied science with mathematics in 10+2. It also suits individuals aspiring for careers in research, data science, finance, or teaching, seeking a rigorous academic foundation. Students passionate about theoretical concepts and their practical implications will thrive here.
Why Choose This Course?
Graduates of this program can expect to pursue various India-specific career paths including data analyst, quantitative researcher, actuarial analyst, or educator. Entry-level salaries typically range from INR 3-6 lakhs per annum, with significant growth potential up to INR 10-15 lakhs for experienced professionals. The strong mathematical base also prepares students for competitive exams, postgraduate studies (M.Sc., Ph.D.), and certifications in data science or financial analytics.
Student Success Practices
Foundation Stage
Master Fundamental Concepts with Practical Tools- (Semester 1-2)
Actively engage with core concepts in Algebra, Calculus, and Real Analysis by solving a wide range of problems. Complement theoretical understanding with hands-on practice using mathematical software like Scilab to visualize and solve problems, especially those from Numerical Methods. Form study groups to discuss challenging topics and learn from peers.
Tools & Resources
Scilab software, Online problem sets (e.g., NPTEL, Khan Academy for basic math), University library resources, Peer study groups
Career Connection
Strong foundational skills are essential for all advanced mathematical applications and interviews for analytical roles. Proficiency in Scilab provides an early edge in computational mathematics.
Develop Robust Programming and Documentation Skills- (Semester 1-2)
Alongside theoretical subjects, dedicate significant time to learning Python programming and LaTeX documentation. Python''''s versatility (covered in GE) is crucial for data analysis and scientific computing, while LaTeX (SEC) is indispensable for professional mathematical typesetting in academic and research settings. Work on small coding projects applying mathematical concepts.
Tools & Resources
Python IDEs (Jupyter, VS Code), Online Python tutorials (Codecademy, Coursera), LaTeX editors (Overleaf), University computing labs
Career Connection
Python is a key skill for data science, machine learning, and quantitative finance roles. LaTeX proficiency is highly valued in research and academic publications, showcasing attention to detail.
Engage in Early-Stage Internships & Workshops- (Semester 1-2)
Proactively seek out and complete the mandated mathematical internships, even if they are short-term. Participate in university-organized workshops or external introductory sessions on topics like Introduction to Data Analytics or Basics of Financial Modeling. This exposure helps connect classroom learning to real-world applications and identifies areas of interest.
Tools & Resources
University career services, LinkedIn for internship searches, Workshop announcements on university portal
Career Connection
Early exposure clarifies career interests, builds a professional network, and provides resume-worthy experience, making future placements easier.
Intermediate Stage
Deepen Theoretical Understanding and Model Real-World Problems- (Semester 3-5)
Focus on advanced subjects like Abstract Algebra, Complex Analysis, and Topology. Simultaneously, leverage Mathematical Modelling and Operations Research courses to apply theoretical knowledge to solve complex real-world problems. Actively participate in case studies and apply optimization techniques to business scenarios.
Tools & Resources
MATLAB/Octave for modeling, OR-specific software (e.g., LINGO, Gurobi for academic use), Research papers on mathematical applications
Career Connection
Develops strong analytical and problem-solving skills, crucial for roles in research & development, logistics, supply chain optimization, and data science.
Build a Data Science Portfolio with Python- (Semester 4-5)
Beyond basic Python, master libraries like NumPy, Pandas, and Matplotlib (SEC-5: Python for Data Science). Work on mini-projects, participate in hackathons, and contribute to open-source projects. Focus on data cleaning, analysis, and visualization. Use tools like Tableau/Power BI (AEC-2: Data Visualization) to create compelling visual narratives from data.
Tools & Resources
Kaggle datasets, GitHub for portfolio, Tableau Public, Python libraries documentation
Career Connection
Directly prepares for roles as Data Analyst, Business Intelligence Analyst, or Junior Data Scientist, highly sought after in the Indian tech market.
Explore Specializations and Network Actively- (Semester 5)
Utilize discipline electives (Financial Mathematics, Discrete Mathematics, Bio Mathematics) to explore potential career paths. Attend seminars, guest lectures, and industry events (online/offline) to network with professionals. Seek mentors in areas of interest and understand current industry trends and skill demands.
Tools & Resources
LinkedIn, University alumni network, Industry-specific forums, Professional body events
Career Connection
Helps refine career goals, gain insights into specific industries, and open doors to internship and full-time job opportunities through networking.
Advanced Stage
Undertake a High-Impact Research Project or Capstone- (Semester 5-6)
Dedicate significant effort to the Research Project (Semester 5) and advanced internships. Choose a topic that aligns with career aspirations and allows for in-depth application of learned mathematical and computational skills. Aim for a publishable-quality report or a project with tangible outcomes, potentially leveraging Blockchain Technology concepts (SEC-6).
Tools & Resources
Academic databases, Research methodology guides, Faculty mentors, Advanced statistical software
Career Connection
A strong research project is a major differentiator for higher studies (M.Sc./Ph.D.) and specialized R&D roles. It demonstrates independent thinking and problem-solving.
Master Advanced Elective Areas for Career Focus- (Semester 6)
Deep dive into the chosen discipline electives (e.g., Number Theory for cryptography, Tensor Analysis for physics/engineering applications, Metric Space for theoretical foundations) to build specialized expertise. Continuously practice problem-solving and critical thinking in these advanced areas.
Tools & Resources
Advanced textbooks, Online courses from NPTEL or edX/Coursera, Relevant research journals
Career Connection
Specialization makes candidates highly valuable for niche roles in finance, cryptography, scientific computing, or academia, offering higher entry salaries and faster growth.
Aggressively Prepare for Placements and Further Studies- (Semester 6)
Engage in mock interviews, aptitude tests, and resume-building workshops offered by the university''''s placement cell. Practice coding challenges, quantitative aptitude, and communication skills. For those aiming for higher studies, prepare for entrance exams like JAM, GATE, or international GRE/TOEFL. Leverage the final internship (Internship-5) to secure a pre-placement offer.
Tools & Resources
Placement cell resources, Online platforms for aptitude and coding practice (e.g., HackerRank, LeetCode), Coaching institutes for entrance exams
Career Connection
Maximizes chances of securing desirable placements in leading companies or admission to top-tier postgraduate programs immediately after graduation.
Program Structure and Curriculum
Eligibility:
- A candidate should have passed HSC (10+2) examination with Science or equivalent examination with at least 45% marks (40% for SC/ST/SEBC) from Gujarat Secondary & Higher Secondary Education Board, or any other board recognized by Marwadi University.
Duration: 3 years / 6 semesters
Credits: 130 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010101 | Algebra | Major | 4 | Matrices and Determinants, Rank of a Matrix, Vectors, Group Theory, Subgroups and Cyclic Groups |
| 01010102 | Calculus-I | Major | 4 | Limits and Continuity, Differentiation, Applications of Derivatives, Integration, Definite and Indefinite Integrals |
| 01010103 | Differential Equations | Generic Elective | 4 | First Order Differential Equations, Second Order Linear Equations, Applications of First and Second Order ODEs, Series Solutions |
| 01010104 | Environmental Science | Ability Enhancement Compulsory Course | 2 | Environmental Pollution, Ecosystems, Biodiversity, Natural Resources, Environmental Management |
| 01010105 | Digital Literacy | Value Added Course | 2 | Computer Fundamentals, Internet and Web Browsing, Digital Communication, Data Security, Productivity Tools |
| 01010106 | Mathematical Software (Scilab) | Skill Enhancement Course | 4 | Introduction to Scilab, Matrix Operations, Plotting, Loops and Conditionals, Solving Equations in Scilab |
| 01010107 | Mathematical Internship | Internship | 2 | Application of mathematical concepts in real-world problems |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010201 | Real Analysis-I | Major | 4 | Real Number System, Sequences and Series, Limits of Functions, Continuity, Differentiability |
| 01010202 | Numerical Methods | Major | 4 | Root Finding Methods, Interpolation, Numerical Differentiation, Numerical Integration, Solving Systems of Linear Equations |
| 01010203 | Programming in Python | Generic Elective | 4 | Python Basics, Data Structures, Functions, Object-Oriented Programming, File Handling |
| 01010204 | English Communication | Ability Enhancement Compulsory Course | 2 | Grammar and Vocabulary, Listening Skills, Speaking Skills, Reading Comprehension, Writing Skills |
| 01010205 | Critical Thinking & Problem Solving | Value Added Course | 2 | Logic and Reasoning, Problem Definition, Solution Generation, Decision Making, Evaluation of Arguments |
| 01010206 | LaTeX | Skill Enhancement Course | 4 | Introduction to LaTeX, Document Structure, Mathematical Typesetting, Tables and Figures, Presentations with Beamer |
| 01010207 | Mathematical Internship | Internship | 2 | Practical application and project work in mathematics |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010301 | Abstract Algebra | Major | 4 | Groups and Subgroups, Normal Subgroups and Quotient Groups, Homomorphisms, Rings and Fields, Integral Domains |
| 01010302 | Mathematical Modelling | Major | 4 | Introduction to Modelling, Compartmental Models, Population Dynamics, Epidemic Models, Optimization Models |
| 01010303 | Probability and Statistics | Generic Elective | 4 | Probability Theory, Random Variables, Probability Distributions, Descriptive Statistics, Inferential Statistics |
| 01010304 | Indian Constitution | Ability Enhancement Course | 2 | Preamble and Basic Features, Fundamental Rights, Directive Principles, Union and State Government, Judiciary |
| 01010305 | Combinatorics | Skill Enhancement Course | 4 | Permutations and Combinations, Generating Functions, Recurrence Relations, Inclusion-Exclusion Principle, Graph Theory Basics |
| 01010306 | Mathematical Internship | Internship | 2 | Industry-relevant problem-solving with mathematical techniques |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010401 | Complex Analysis | Major | 4 | Complex Numbers, Analytic Functions, Complex Integration, Series Expansions, Residue Theory |
| 01010402 | Linear Algebra | Major | 4 | Vector Spaces, Linear Transformations, Eigenvalues and Eigenvectors, Inner Product Spaces, Orthogonality |
| 01010403 | Graph Theory | Generic Elective | 4 | Basic Graph Concepts, Trees, Connectivity, Eulerian and Hamiltonian Graphs, Planar Graphs |
| 01010404 | Data Visualization | Ability Enhancement Course | 2 | Principles of Visualization, Types of Charts, Tools for Visualization, Data Storytelling, Interactive Dashboards |
| 01010405 | Operations Research | Skill Enhancement Course | 4 | Linear Programming, Simplex Method, Duality, Transportation Problem, Assignment Problem |
| 01010406 | Mathematical Internship | Internship | 2 | Applied mathematical projects and problem-solving |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010501 | Topology | Major | 4 | Topological Spaces, Open and Closed Sets, Continuous Functions, Connectedness, Compactness |
| 01010502 | Differential Geometry | Major | 4 | Curves in Space, Surfaces, First and Second Fundamental Forms, Curvature, Geodesics |
| 01010503 | Financial Mathematics | Discipline Elective | 4 | Interest Rates, Annuities, Bonds, Derivatives Pricing, Portfolio Optimization |
| 01010504 | Fuzzy Mathematics | Discipline Elective | 4 | Fuzzy Sets, Fuzzy Logic, Fuzzy Relations, Fuzzy Arithmetic, Applications of Fuzzy Sets |
| 01010505 | Discrete Mathematics | Discipline Elective | 4 | Logic and Proofs, Sets and Relations, Functions, Counting Techniques, Recurrence Relations |
| 01010506 | Bio Mathematics | Discipline Elective | 4 | Population Growth Models, Disease Dynamics, Pharmacokinetics, Biological Networks, Biostatistics |
| 01010507 | Python for Data Science | Skill Enhancement Course | 4 | NumPy, Pandas, Matplotlib, Data Cleaning, Data Analysis, Exploratory Data Analysis, Introduction to Machine Learning Libraries |
| 01010508 | Research Project | Project | 6 | Research Methodology, Literature Review, Data Collection and Analysis, Report Writing, Presentation of Findings |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 01010601 | Functional Analysis | Major | 4 | Normed Linear Spaces, Banach Spaces, Hilbert Spaces, Linear Operators, Dual Spaces |
| 01010602 | Number Theory | Discipline Elective | 4 | Divisibility and Euclidean Algorithm, Congruences and Modular Arithmetic, Prime Numbers and Factorization, Diophantine Equations, Applications in Cryptography |
| 01010603 | Tensor Analysis | Discipline Elective | 4 | Tensors and Their Properties, Tensor Operations, Metric Tensor, Covariant Differentiation, Applications in Physics and Engineering |
| 01010604 | Metric Space | Discipline Elective | 4 | Metric Spaces, Open and Closed Sets, Convergence and Completeness, Compactness, Connectedness |
| 01010605 | Integral Transforms | Discipline Elective | 4 | Laplace Transform, Fourier Transform, Z-Transform, Inverse Transforms, Applications to Differential Equations |
| 01010606 | Block Chain Technology | Skill Enhancement Course | 4 | Cryptography Fundamentals, Distributed Ledgers, Smart Contracts, Consensus Mechanisms, Blockchain Applications |
| 01010607 | Mathematical Internship | Internship | 4 | Advanced project development and industrial experience in mathematics |
