01
AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
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Five outcome-based courses
Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
02
Responsible AI User
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
03
AI at Work
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
04
AI Policy & Society
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
05
Building with AI Systems
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
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FundamentalsCore concepts: how AI works at a high level.84 guides Language AILLMs, NLP, ChatGPT, prompting, and text understanding.155 guides Visual AIImage generation, computer vision, video, and design.133 guides Audio AIVoice, music, podcasting, and audio-first AI.117 guides CompaniesProfiles of OpenAI, Anthropic, Google, Meta, and more.121 guides ApplicationsHow AI shows up in coding, search, agents, and daily life.111 guides IndustriesAI in healthcare, finance, education, energy, and more.91 guides TechnicalChips, fine-tuning, RAG, vectors, and AI infrastructure.177 guides SocietyBias, privacy, copyright, safety, and the AI future.30 guides
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Technical
Toolformer and Self-Taught Tool Use
Toolformer is a 2023 Meta AI method that lets a language model teach itself when and how to call external tools like calculators, search engines…
TechnicalVoyager Minecraft Agent and Skill Library
Learn how Voyager works: a Minecraft AI agent that writes code, stores reusable skills, and improves through lifelong learning without gradient updates.
TechnicalGenerative Agents and Simulated Societies
Generative agents are AI characters powered by language models that remember, plan, and react like believable people.
TechnicalEpisodic and Semantic Agent Memory
AI agents need two kinds of long-term memory: episodic memory for specific past events and semantic memory for general facts.
TechnicalHidden Markov Models
A Hidden Markov Model describes a system that moves through hidden states you cannot see directly, emitting observable outputs along the way.
TechnicalGaussian Processes
A Gaussian Process is a flexible, nonparametric way to model functions that comes with built-in uncertainty estimates.
TechnicalQ-Learning
Q-Learning is a reinforcement learning algorithm that teaches an agent which actions pay off best by gradually learning the value of each move through trial…
TechnicalActor-Critic Methods
Actor-Critic methods combine two learners: an 'actor' that chooses actions and a 'critic' that judges how good those actions were.
TechnicalMonte Carlo Tree Search
Monte Carlo Tree Search (MCTS) is a planning algorithm that decides the best move by selectively building a search tree and simulating many possible futures.
TechnicalAdam and Adaptive Optimizers
Adam is the workhorse optimizer behind most modern neural networks, automatically tuning a separate learning rate for every parameter.
TechnicalLearning Rate Scheduling
A learning rate schedule changes the step size during training instead of holding it fixed.
TechnicalLayer Normalization
Layer normalization stabilizes training by rescaling the activations within each individual example so they have zero mean and unit variance.
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