"Mathematical Foundatiouns of AI" offers a rigorous introduction to the fundamental concepts of linear algebra, calculus, and optimization theory that form the mathematical basis of machine learning, data science, deep learning, and artificial intelligence. It explores key topics including a comprehensive treatment of vectors and matrices, dimensionality reduction techniques, and a range of optimization methods, from approaches for unconstrained and constrained problems to iterative algorithms.
What you'll learn
understanding of linear algebra concepts
knowledge of calculus applications in AI
ability to apply optimization methods to problems
familiarity with dimensionality reduction techniques
Course objectives
teach fundamental mathematical concepts related to AI
explore optimization methods for machine learning
provide a solid foundation for further study in data science and AI