Intermediate
AI Engineer
From your first model to generative AI in production.
- 1Intro to Machine Learning
- 2Intro to Deep Learning
- 36.034 Artificial Intelligence
- +1 more
Start path5–8 months part-time
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AI & Machine Learning
6.034 Artificial Intelligence
Patrick Winston's celebrated MIT lectures on how intelligence can be represented.
Free to enrolAdvancedNo certificateAdded 22 Jun 2026
Rating4.8 / 53k reviews
Duration60 hrsprovider estimate
Lessons23modules
Learners290kenrolled
MIT
MIT OpenCourseWare
University
No certificates — OpenCourseWare publishes materials, not enrolment.
About this course
A full semester of MIT's classical AI subject: search, constraint satisfaction, rule-based systems, learning, neural networks and support vector machines. The lectures are famous for explaining ideas rather than reciting equations, and remain some of the best-taught material in the field.
What you'll learn
- Implement search and constraint-satisfaction algorithms
- Represent knowledge with rules and semantic nets
- Understand learning from a first-principles view
- Explain how SVMs and neural nets actually decide
Syllabus
- 1Reasoning: goal trees and problem solving10 hrs
- 2Search: depth-first, A*, games12 hrs
- 3Constraints and visual object recognition10 hrs
- 4Learning: identification trees and neural nets16 hrs
- 5Support vector machines and boosting12 hrs
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