About Course
Mathematical Foundations for AI and Algorithmic Thinking is a comprehensive course designed to build the core mathematical intuition required for Artificial Intelligence, Machine Learning, and advanced algorithms. Master the mathematical pillars of AI—Discrete Mathematics, Calculus, Probability, and Linear Algebra. Learn to transform abstract formulas into practical tools for building intelligent technology. Explore the ideas behind intelligent systems through hands-on mathematical modeling connecting theory to neural networks, optimization, probabilistic learning, and high-dimensional data. This journey is designed to turn mathematical principles into clarity, confidence, and creative problem-solving, whether your path leads to Machine Learning, Data Science, competitive programming, or AI research.
Who can join?
- BS (CS/SE/AI/Data Science) students who have completed at least 2 years of study
- Graduates and professionals who want to strengthen or refresh their mathematical foundations
- AI, Machine Learning, and Data Science learners who want to understand the mathematics behind AI systems
- Software developers and programmers looking to improve their algorithmic and mathematical reasoning
- Aspiring AI/ML engineers preparing for advanced work in machine learning and computational systems
- Students preparing for advanced courses involving algorithms, optimization, probability, and linear algebra
Whether you are beginning your AI journey, preparing to enter the job market, or upgrading your technical depth, this course builds the mathematical foundation needed to understand and develop AI systems. You will explore four core areas of mathematics for AI and Computer Science: Discrete Mathematics, Calculus, Linear Algebra, and Probability & Statistics.
Course Content
MONTH 1 Discrete Mathematics, Probability & Statistics for AI
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WEEK 1 – Proofs And Why they Matters?
02:13:24 -
WEEK 1 Lab Session – Building Mental Muscle for Mathematical Proofs
53:31 -
WEEK 2 – Mathematical Induction, Recursion & Algorithm Correctness
02:03:43 -
WEEK 2 Lab Session – Solving Assignment: Mathematical Induction
58:49
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