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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Language AI
Repetition Penalty and Decoding Controls
Decoding controls are the knobs that decide how a language model picks each next word from its probability distribution.
Language AIALiBi Position Bias
ALiBi (Attention with Linear Biases) is a clever way to give transformers a sense of word order without traditional position embeddings.
Language AIMulti-Query Attention
Multi-Query Attention (MQA) is a memory-saving twist on transformer attention that shares one set of keys and values across all attention heads.
Language AISentencePiece Tokenization
SentencePiece is a language-agnostic tokenizer that learns how to split raw text into subword pieces directly from data, without relying on spaces.
Language AIWordPiece Tokenization
WordPiece is the subword tokenization algorithm that powers BERT and many Google models, splitting words into reusable fragments so a model can handle any…
Language AISentence-BERT Embeddings
Sentence-BERT (SBERT) adapts BERT to produce a single fixed-length vector for an entire sentence, so meaning can be compared with fast cosine similarity.
Language AIT5 and Text-to-Text Transfer
T5 (Text-to-Text Transfer Transformer), from Google in 2019, reframes every NLP task, translation, summarization, classification, even regression, as feeding…
Language AIDense Passage Retrieval
Dense Passage Retrieval (DPR) finds relevant text by comparing the meaning of a question and passages as numeric vectors, not matching words.
Language AIBM25 and Lexical Retrieval
BM25 is the classic keyword-based ranking function that scores documents by how often query terms appear, adjusted for term rarity and document length.
Language AIHyDE Hypothetical Document Embeddings
HyDE improves retrieval by first asking a language model to imagine a fake answer document, then searching with that document's embedding instead of the raw…
Language AISpeculative Decoding Draft Models
Speculative decoding uses a small, fast 'draft' model to guess several upcoming tokens that a large model then verifies in one pass.
Language AILookahead Decoding
Lookahead decoding speeds up LLM generation without any extra draft model by guessing and verifying multiple future tokens in parallel using n-grams…
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