20 Free AI and Machine Learning Courses Worth Watching
Not our content — these are YouTube courses from Stanford, MIT, DeepMind, fast.ai, and independent researchers. We've covered AI for 11 years and 476 issues; these are the ones we'd actually send to a friend who wants to learn AI.
Machine Learning Fundamentals
Caltech CS156: Learning from Data
AdvancedCaltech's Yaser Abu-Mostafa teaches you the mathematical theory behind why machine learning works — VC dimension, bias-variance tradeoffs, regularizat...
Stanford CS229: Machine Learning
IntermediateAndrew Ng covers the core math and algorithms behind supervised learning, unsupervised learning, and reinforcement learning in this Stanford classic. ...
StatQuest: Machine Learning
BeginnerJosh Starmer breaks down decision trees, random forests, gradient boosting, PCA, cross-validation, and core statistics using simple drawings and plain...
Deep Learning
CMU Introduction to Deep Learning (11-785)
AdvancedCarnegie Mellon takes you from basic multilayer perceptrons through attention mechanisms, GANs, variational autoencoders, and self-supervised learning...
MIT 6.S191: Introduction to Deep Learning
IntermediateMIT walks you through neural networks, convolutional and recurrent architectures, generative models, and large language models in a fast-paced format ...
Neural Networks: Zero to Hero
IntermediateAndrej Karpathy walks you through building neural networks, backpropagation, and eventually a GPT-style language model entirely from scratch in Python...
NYU Deep Learning SP21 (Yann LeCun)
AdvancedTuring Award winner Yann LeCun shares his distinctive perspective on energy-based models, self-supervised learning, world models, and where AI is head...
Practical Deep Learning for Coders
BeginnerJeremy Howard has you building working deep learning models from the very first lesson — image classifiers, NLP pipelines, tabular models — and fills ...
Stanford CS230: Deep Learning
IntermediateAndrew Ng covers convolutional networks, recurrent architectures, optimization methods like Adam and BatchNorm, generative adversarial networks, and e...
Stanford CS330: Deep Multi-Task and Meta Learning
AdvancedChelsea Finn teaches multi-task learning, transfer learning, meta-learning algorithms like MAML, prototypical networks, and few-shot learning at Stanf...
Natural Language Processing & LLMs
Hugging Face NLP Course
IntermediateHugging Face walks you through their Transformers library hands-on: tokenization, fine-tuning pretrained models, text classification, named entity rec...
Stanford CS224N: NLP with Deep Learning
AdvancedStanford takes you deep into word vectors, transformer architectures, attention mechanisms, pretraining strategies, and models like BERT and GPT. Aime...
Stanford CS25: Transformers United
AdvancedResearchers from OpenAI, Google Brain, DeepMind, and Anthropic present cutting-edge work on transformer architectures, scaling laws, multimodal AI, an...
Computer Vision
Stanford CS231N: Convolutional Neural Networks for Visual Recognition
AdvancedStanford covers image classification, object detection, semantic segmentation, and generative models while teaching you to visualize what convolutiona...
Reinforcement Learning
DeepMind Reinforcement Learning Lecture Series
AdvancedHado van Hasselt from DeepMind teaches multi-armed bandits, Markov decision processes, policy gradient methods, and deep reinforcement learning at UCL...
Stanford CS234: Reinforcement Learning
AdvancedEmma Brunskill covers Markov decision processes, policy evaluation, Q-learning, deep reinforcement learning, exploration strategies, and imitation lea...
AI Explainers & Paper Reviews
3Blue1Brown: Neural Networks
BeginnerGrant Sanderson uses his signature animations to visually explain gradient descent, backpropagation, and how neural networks actually learn from data....
5-10 min each
Two Minute Papers
BeginnerKaroly Zsolnai-Feher distills cutting-edge AI research papers into short, visual breakdowns you can watch in a few minutes. Perfect for anyone in the ...
MLOps & Production
Machine Learning Engineering for Production (MLOps)
IntermediateAndrew Ng teaches you how to take machine learning models from Jupyter notebooks into production — covering ML pipelines, data management, model monit...
MIT Introduction to Data-Centric AI
IntermediateMIT teaches you the emerging paradigm of improving AI by fixing your data rather than tweaking models — covering data quality, labeling strategies, au...