Courses

This page features courses I published as edited videos or as a book. If you’re looking for courses offered via live lectures, check out my Talks page.

Transformer Architectures for Generative A.I.

My latest courses apply deep learning to the training and deployment of Large Language Models like GPT architectures in order to process natural language, particularly for Generative A.I. applications:

• Generative AI with LLMs: Hands-On Training featuring Hugging Face and PyTorch Lightning (100% free)

• NLP with ChatGPT (and other LLMs)

Deep Learning

My book Deep Learning Illustrated serves as an introductory course on neural networks and artificial intelligence. I partitioned the book into three separate video courses, all available via O’Reilly:

• Deep Learning with TensorFlow, Keras, and PyTorch (free sample here)

• Deep Learning for Natural Language Processing (free sample here)

• Machine Vision, GANs, and Deep Reinforcement Learning (free machine vision and deep RL samples)

Machine Learning Foundations

Four subject areas across the fields of mathematics and computing provide strong foundations for understanding and applying machine learning theory. My curriculum and accompanying open-source code for learning about all of these subject areas is detailed in my Machine Learning Foundations GitHub repository. To enable you to study the subject areas individually depending on your interests, I’ve broken up my broad ML Foundations curriculum into four standalone courses by subject area:

Linear Algebra

• YouTube version

• O’Reilly version (free sample here)

Calculus

• YouTube version

• O’Reilly version (free sample here)

Probability and Statistics

• YouTube version (in active development)

• O’Reilly version (free sample here)

Computer Science

• O’Reilly version (free sample here)

• YouTube version forthcoming