Maths

Major: Mathematics (Matematik)

Program Overview: A rigorous, theoretical, and applied program covering pure mathematics, applied mathematics, and computational techniques. Designed to develop analytical thinking, problem-solving, and quantitative skills for careers in academia, finance, technology, and research. Aligns with global mathematical standards and modern applications in data science, cryptography, and engineering.

Key Learning Objectives:

• Master core mathematical disciplines (algebra, calculus, geometry, number theory).
• Develop skills in applied mathematics (statistics, operations research, mathematical modeling).
• Learn computational mathematics (algorithms, numerical analysis, programming).
• Explore mathematical applications in physics, engineering, economics, and data science.
• Gain expertise in mathematical software (MATLAB, Mathematica, Python, R).
• Understand mathematical proofs and abstract reasoning.
• Apply mathematics to real-world problems (cryptography, finance, AI).

Core Courses:

1. Calculus & Mathematical Analysis
   • Limits, derivatives, integrals, and multivariate calculus.
2. Linear Algebra & Abstract Algebra
   • Vector spaces, matrices, group theory, and ring theory.
3. Differential Equations
   • Ordinary and partial differential equations with applications.
4. Probability & Statistics
   • Statistical methods, distributions, and hypothesis testing.
5. Discrete Mathematics
   • Combinatorics, graph theory, and logic.
6. Numerical Analysis & Computational Mathematics
   • Algorithms, numerical methods, and scientific computing.
7. Mathematical Modeling
   • Modeling real-world systems in physics, biology, and economics.
8. Cryptography & Number Theory
   • Encryption, prime numbers, and modern cryptographic techniques.
9. Operations Research
   • Optimization, linear programming, and decision-making models.
10. Practicum in Applied Mathematics
    • Projects in data science, finance, or engineering applications.
11. Capstone Project
    • Research thesis or applied project (e.g., algorithm development, financial modeling).

Assessment Methods:

• Mathematical proofs and problem sets
• Computational projects (coding, simulations)
• Statistical analysis reports
• Mathematical modeling case studies
• Capstone project presentations

Tools & Resources:

• Software: MATLAB, Mathematica, Python (NumPy, SciPy), R, LaTeX
• Books:
  • Calculus by Michael Spivak
  • Linear Algebra Done Right by Sheldon Axler
  • Introduction to Probability by Joseph K. Blitzstein
  • A Book of Abstract Algebra by Charles C. Pinter

Prerequisites:

Strong background in high school mathematics (algebra, geometry, calculus). Logical reasoning and problem-solving skills.

Program Duration:

4 years (bachelor’s), including research projects or internships.

Certifications (Optional):

• Actuarial Exams (SOA/CAS) – For insurance/finance careers
• Certified Analytics Professional (CAP) – For data science roles
• MATLAB/ Python Certifications – For computational mathematics

Career Paths:

• Data Scientist (analytics, machine learning, AI)
• Actuary (insurance, risk assessment)
• Financial Analyst/Quant (banking, investment firms)
• Cryptographer (cybersecurity, blockchain)
• Operations Research Analyst (logistics, supply chain)
• Academic Researcher/Professor (universities, research institutes)
• Software Engineer (algorithms, computational mathematics)

Why This Major?

Mathematics is the foundation of science, technology, and finance, making it one of the most versatile degrees. This program develops critical thinking and problem-solving skills applicable to high-demand fields like data science, finance, and AI. Graduates can pursue careers in tech, academia, or industry, with opportunities for advanced study (master’s/PhD). Ideal for students who enjoy logic, abstraction, and real-world applications of mathematical principles.