Math, Python, and Machine Learning Foundations for Data Science

Transitioning into data science and artificial intelligence requires a strong grasp of both foundational mathematics and modern Python tools. This text-based course guides you through essential mathematical concepts, programming fundamentals, and introductory machine learning principles. What you'll learn: Understand key mathematical foundations, including linear algebra, calculus, and probability for data analysis; Master Python programming basics, data structures, and essential type hints; Apply key data manipulation concepts with standard data libraries; Learn the core mechanics of supervised and unsupervised machine learning algorithms; Explore basic developer tools, version control with Git, and clean code principles; Evaluate machine learning model performance using standard metrics. The course begins with foundational terminology, key definitions, and core mathematical theory before introducing practical Python code and machine learning workflows. Designed for beginners, self-taught programmers, and applicants preparing for technical programs who want to build confidence in math and coding. Start reading today to lay a clear, structured foundation for your data science journey.