Suggested preparation: Background in neuroscience, psychology, computing or related quantitative study.
Optional preparation: Free MIT Course: Artificial Intelligence: Search, Reasoning and Learning.
About this course
Explore connections among neuroscience, cognition and artificial intelligence. This lecture collection presents research perspectives on learning, brain measurement, information and computational models of vision.
Topics and lesson examples
- Lecture 0: Tomaso Poggio – Introduction to Brains, Minds, and Machines
- Seminar 3: Jessica Sommerville – Infants' Sensitivity to Cost and Benefit
- Lecture 7.5: Hynek Hermansky – Auditory Perception in Speech Technology, Part 2
- Tutorial 3.2: Lorenzo Rosasco – Machine Learning Part 2
- David Rolnick & Ishita Dasgupta: Modeling Dynamic Memory with Hopfield Networks
Course at a glance
| Provider | MIT |
|---|---|
| Platform | YouTube · MIT OpenCourseWare |
| Access | Free Video |
| Level | Professional — WikiFree study-level assessment |
| Language | English |
| Available lessons | 60 |
| Video duration | 46h 30m · self-paced |
| Details checked | 10 October 2026 |
Preparation and study approach
Suggested preparation: Background in neuroscience, psychology, computing or related quantitative study.
Follow the available videos in sequence, pausing to summarize the main argument or reconstruct a worked example. Keep a short list of assumptions, unfamiliar terms and questions to revisit. Additional reading, problem solving and practice will take time beyond the listed video duration.
Using this video classroom
Select a lesson from the list, or search for a topic. Previous and Next move through the sequence. You can mark lessons complete; progress is stored in this browser without a WikiFree account.
Free access and course scope
The public MIT OpenCourseWare videos in this classroom are free to watch. This listing provides the available playlist recordings, which may include selected lectures, recitations, demonstrations or supporting discussions rather than every component of the original campus course. Textbooks, equipment, software licenses, supervised labs, graded assignments and instructor feedback are not supplied by WikiFree. No purchase is required to watch the videos or use the note-based study approach above.
WikiFree independently organizes these resources for self-paced study. Watching does not award an MIT certificate, academic credit or admission to MIT.
Video provider and credit: MIT OpenCourseWare on YouTube. WikiFree titles, descriptions and cover artwork are independently prepared.
Related courses for your next step
- Review a lower-level optionFree MIT Course: Artificial Intelligence: Search, Reasoning and Learning
Focus: 1. Introduction and Scope · 8. Constraints: Search, Domain Reduction
Intermediate - Review a lower-level optionFree AI Fundamentals Course: Machine Learning Concepts
Focus: Understand the purpose of machine learning · Explore how a model learns from examples
Beginner - Review a lower-level optionFree AI Fundamentals Course: Machine Learning and Generative AI
Focus: AI fundamentals · Machine-learning concepts
Beginner
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free MIT Course: Brains, Minds and Artificial Intelligence | Professional | Lecture 0: Tomaso Poggio - Introduction to Brains, Minds, and Machines · Seminar 3: Jessica Sommerville - Infants' Sensitivity to Cost and Benefit · Lecture 7.5: Hynek Hermansky - Auditory Perception in Speech Technology, Part 2 | 46h 30m of video; practice time is additional |
| Free MIT Course: Artificial Intelligence: Search, Reasoning and Learning | Intermediate | 1. Introduction and Scope · 8. Constraints: Search, Domain Reduction · 14. Learning: Sparse Spaces, Phonology | 24h 17m of video; practice time is additional |
| Free AI Fundamentals Course: Machine Learning Concepts | Beginner | Understand the purpose of machine learning · Explore how a model learns from examples · Recognize a classification problem | 34m of video; practice time is additional |
| Free AI Fundamentals Course: Machine Learning and Generative AI | Beginner | AI fundamentals · Machine-learning concepts · Deep learning | 11h 45m of video; practice time is additional |
Provider: MIT. Videos play from the MIT OpenCourseWare channel on YouTube.
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