Stanford Online: Stanford CS229: Machine Learning Course (YouTube)
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical advice); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing. For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai
- Date created
- May 21, 2026
- Specialty level
- Intermediate
- Training category
- External Course
- Provider
- Stanford Online/YouTube
- Timeline
- Self-paced, but full listing of videos is 26 hours and 24 minutes.
- Cost
- Free
Course intelligence
Expected end-productTraining Resource
Intended goalsNot specified
PrerequisitesN/A, but should probably have a good math background
Recommended whenYou have an interest in getting the deep details of machine learning from a broad perspective, and have a mathematical background as well.
ApplicabilityAnything with AI/ML
Certification examNo exam listed