Foundations of Machine Learning and Data Science

Machine learning powers modern technology, driving innovations across data science and artificial intelligence. This written course offers a clear, structured entry point into the fundamental concepts and practical methodologies of machine learning. You will gain a solid understanding of core algorithms, learn how to prepare datasets, and explore modern artificial intelligence workflows through clear written explanations and code examples. What you'll learn: • Understand core machine learning terminology, foundational math concepts, and learning paradigms • Prepare and clean datasets using modern data manipulation techniques • Apply supervised and unsupervised learning algorithms to practical problems • Evaluate model performance using key metrics like precision, recall, and accuracy • Grasp the basics of neural networks and foundation model architectures • Implement structured machine learning workflows using clean Python code snippets. The course begins with foundational definitions, core terminology, and basic data principles before guiding you through model selection and training logic. It is tailored for absolute beginners who want a practical, clear understanding of data science without prerequisites. Read through the modules to start building your skills in artificial intelligence today.