These AI Skills Are the Most Valuable // TRAIN BRAIN

These AI Skills Are the Most Valuable

Learn details about our Generative AI: Technology, Society, and Business Program ➡️ https://stanford.io/Gen-AI
Professor James Landay, Co-Founder and Co-Director of the Stanford Institute for Human-centered Artificial Intelligence (HAI), explains the AI skills that matter most.

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Webinar: AI Agent Simulation of Human Behavior with Michael Bernstein

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How AI Coding Agents Are Changing Software Development

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Overview: Stanford CME295 Transformers and Large Language Models

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 19: Model-Based RL

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 18: RL Policy Optimization

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 17: RL Value-Based Methods

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 16: Fundamentals of RL

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 15: Imitation Learning

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 14: Intro to IL and RL

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 13: Intro to Learning

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 12: Feasibility of MPC

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 11: Introduction to MPC

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 10: Reachibility Analysis

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 9: Stochastic Dyn. Program

AStanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 8: Nonlinearity

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 7: Dynamic Programming

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 6: Optimal Control

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 5: Computational Methods

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 4: Optimal Control

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 3: Calculus of Variations

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 2: Optimization Theory

Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 1: Course Overview

Stanford CS329A Self-Improving AI Agents | Part 4 | Learning from Feedback with Tools/Code

Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview

Stanford CS329A Self-Improving AI Agents | Part 2 | Test-Time Compute Scaling

Stanford CS329A Self-Improving AI Agents | Part 3 | Robust Verification

Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL

Stanford CS329A Self-Improving AI Agents | Part 7 | Self-Improvement and Deep Research Agents

Stanford CS329A Self-Improving AI Agents | Part 5 | Planning and Multi-Step Reasoning

Stanford CS329A Self-Improving AI Agents | Part 9 | Future Research Areas

Stanford CS329A Self-Improving AI Agents | Part 8 | Agentic Evaluations and Long Horizon Tasks

Stanford CS547 HCI Seminar | Spring 2026 | Show It or Tell It? Text, Visualization, and Combination

Stanford CS229 Machine Learning | Spring 2026 | Lecture 20: GMM (EM), PCA

Stanford CS229 Machine Learning | Spring 2026 | Lecture 18: GMM (EM), PCA

Stanford CS229 Machine Learning | Spring 2026 | Lecture 16: Basic Concept in RL, Policy Gradient

Stanford CS229 Machine Learning | Spring 2026 | Lecture 14: Transformers, In-Context Learning

Stanford CS229 Machine Learning | Spring 2026 | Lecture 13: LLMs, Next-Word Prediction Loss

Stanford CS229 Machine Learning | Spring 2026 | Lecture 12: Representation Learning

Stanford CS229 Machine Learning | Spring 2026 | Lecture 11: Diffusion Models

Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA

Stanford CS229 Machine Learning | Spring 2026 | Lecture 9: K-Means and GMM (non-EM)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 8: Neural Networks 2 (Backprop)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 7: Neural Networks 1 (Architecture)

Stanford CS229 Machine Learning | Spring 2026 | Lecture 6: Dataset Split, ML Advice

Stanford CS229 Machine Learning | Spring 2026 | Lecture 5: Gaussian Discriminant Analysis

Stanford CS229 Machine Learning | Spring 2026 | Lecture 4: Exponential Family, GLMs classification

Stanford CS229 Machine Learning | Spring 2026 | Lecture 3: Weighted Least Squares

Stanford CS229 Machine Learning | Spring 2026 | Lecture 2: Supervised Learning Setup

Stanford CS229 Machine Learning | Spring 2026 | Lecture 1: Introduction

What Is a POMDP?

These AI Skills Are the Most Valuable

James Landay Explains Why AI Should Be Human-Centered

Course Overview: AA228 Decision Making Under Uncertainty

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | The GPU Economy

Stanford Robotics Seminar ENGR319 | Winter 2025 | Embodied Intelligence

Stanford CS547 HCI Seminar | Spring 2026 | Promoting Agency in Human-AI Interaction

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Economics of Generative AI

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, AI in Life Sciences

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Stanford CS547 HCI Seminar | Spring 2026 | Just-in-Time Objectives for Specialized AI Interactions

Stanford CS547 HCI Seminar | Spring 2026 | Toward Ontological Multiplicity in AI and Computing

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrasctructure, Enterprise AI, SaaS

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Stanford Robotics Seminar ENGR319 | Spring 2026 | Towards Trustworthy Autonomy

Our Learners share about their experience in the Engineering Leadership Program