YouTube Courses

Bayesian Networks 1 - Inference - Stanford CS221: AI

Learn how Bayesian networks compactly represent joint distributions and support probabilistic inference, including explaining away, evidence conditioning, and applications in tracking and classification.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Online Course

Algorithmic Governance: Auditing Search and Recommendation Algorithms for Problematic Content

A talk on auditing YouTube and Amazon search and recommendation algorithms to trace how misinformation surfaces and on governing these systems over time.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Convex Optimization I - Lecture 6

A standalone lecture from the first course in convex optimization.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Convex Optimization I - Lecture 8

Lecture 8 from a course on convex optimization.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Convex Optimization I - Lecture 7

A lecture in Stanford’s Convex Optimization I course, taught by electrical engineering professor Stephen Boyd.

• YouTube
• 1 hour 21 minutes
• Self-Paced
• Free Video

Human-Robot Interaction - Enhancing Human Performance with Autonomous Robots

Explore how autonomous robots might work alongside people, understand human intent, and enhance human performance.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Stanford Seminar - Mixture of Experts Paradigm and the Switch Transformer

Explains how the Switch Transformer simplifies sparse expert routing to train trillion-parameter language models faster and with lower computational cost.

• YouTube
• 1 hour 6 minutes
• Self-Paced
• Free Video

Stanford Seminar - Dataflow for Convergence of AI and HPC - GroqChip

Explores how Groq’s tensor streaming processor uses dataflow and deterministic stream programming to scale deep learning computation across chips.

• YouTube
• 1 hour 46 minutes
• Self-Paced
• Free Video

Stanford Seminar - Universal Intelligent Systems by 2030 - Carl Hewitt and John Perry

A vision for universal intelligent systems that combine inconsistent information across everyday devices, adapt through interaction, and track their own goals, capabilities, and provenance.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Information Theory of Deep Learning - Naftali Tishby

Explains deep neural network learning through the Information Bottleneck, linking input compression and mutual information to generalization and accuracy.

• YouTube
• 1 hour 25 minutes
• Self-Paced
• Free Video

From Large Language Models to Large Multimodal Models - Stanford CS25 - Lecture 4

See how large language models are extended to visual perception through multimodal systems for understanding, GUI interaction, and OCR.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Online Communities as Model Systems for Commons Governance

Online communities serve as transparent laboratories for studying how groups build institutions and govern shared resources.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Shaping the Future of AI from the History of Transformer Architectures - Stanford CS25

A historical view of Transformer development examines how cheaper compute reshaped architectures and offers a way to reason about AI’s direction.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Natural Gas: From History to Future Impacts - Understand Energy Lecture

A survey of natural gas traces its history and infrastructure, then examines its environmental effects, economics, and future.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Convex Optimization I - Lecture 10

Stephen Boyd teaches Lecture 10 of Convex Optimization I, a university course focused on convex optimization.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video