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
Hyperparameter Tuning
Hyperparameters are the settings you choose before training, like learning rate or model size, that the model does not learn on its own.
Language AIIn-Context Learning
In-context learning is the surprising ability of large language models to pick up a new task from a few examples placed in the prompt, without any retraining.
Language AIInstruction Tuning
Instruction tuning is the training step that turns a raw text-predictor into a model that actually follows instructions like 'summarize this' or 'write…
Language AIAI Hallucinations
An AI hallucination is when a model states something false as if it were true — a fake citation, a made-up statistic, a wrong fact — fluently and confidently.
Language AITemperature and Sampling
Temperature and sampling are the dials that control how 'random' or 'safe' a language model's wording is.
Language AIWord Embeddings
Word embeddings turn words into lists of numbers so that words used in similar ways end up close together in a mathematical space.
Language AIAttention Mechanisms
Attention lets a model decide which other words in a sentence matter most when interpreting each word.
Language AIContext Windows
A context window is the maximum amount of text — measured in tokens — that a model can read and keep in mind at one time.
Language AIChain-of-Thought Reasoning
Chain-of-thought reasoning is when a model works through a problem step by step in writing before giving its final answer.
Language AIQuantization
Quantization shrinks an AI model by storing its numbers at lower precision, so a model that needed a data-center GPU can sometimes run on a laptop or phone.
Language AIQuestion Answering
Question answering (QA) is the task of getting an AI system to give a direct answer to a question, rather than just a list of links.
Language AIText Classification
Text classification automatically sorts pieces of text into categories, like tagging an email as spam or a review as positive.
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