Artificial Intelligence and Machine Learning Fundamentals

Artificial intelligence and machine learning are transforming every industry, but starting out can feel overwhelming with all the mathematical jargon and complex code. This course simplifies these concepts, guiding you from absolute beginner to a confident practitioner who understands how modern AI systems actually work. You will transition from simply hearing about AI to understanding its inner workings, learning how to select the right models, prepare data, and apply modern AI techniques to solve real-world problems. What you'll learn: Understand core AI and machine learning terminology, including supervised, unsupervised, and reinforcement learning; Apply modern data preparation techniques to clean and structure datasets for training; Evaluate machine learning models using key performance metrics like accuracy, precision, and recall; Explore neural networks and deep learning architectures to understand how modern computer vision and language models function; Practice basic prompt engineering and learn how retrieval-augmented generation (RAG) connects large language models to external data; Navigate the ethical considerations, bias mitigation, and privacy concerns inherent in modern AI development. We begin with essential definitions and foundational mathematical concepts before moving into practical algorithms, data preprocessing, and modern generative AI architectures. This text-only course is designed specifically for beginners with no prior background in data science, computer science, or advanced mathematics. Start your journey into the world of artificial intelligence today and build the skills needed for the future.