Free self-paced course
A free, self-paced course that builds a shared vocabulary for AI.
Many artificial intelligence conversations fail early because basic terms are used inconsistently. This three-part series starts by stabilizing shared language, then builds up to how modern AI systems are designed and evaluated.
Each part is a short click-through lesson with quick knowledge checks along the way. There's no login and no grading — answer each check correctly to move on, and your progress is saved in this browser.
Part 1
How AI, machine learning, deep learning, and neural networks relate; what a model is; why architecture matters; and the three ways models learn.
Part 2
The major AI domains (NLP, computer vision, robotics, RAG), how generative AI creates new content, and where the field is heading with agentic AI, AGI, and AI safety.
Part 3
Why specialized hardware like GPUs matters, where AI runs (cloud, on-prem, edge), and how models are trained, evaluated, and optimized for inference.
