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657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

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657 tutors

Shot Planning and Storyboards for AI Video

Shot Planning and Storyboards for AI Video

Plan every shot before you generate, so clips cut together into a storyIntermediateImage and video AI4.7(3)53 lessonsSample
Ruth Okafor$6
Loss functions: what your model is minimising

Loss functions: what your model is minimising

Understand MSE, cross entropy and friends well enough to choose, read and debug themBeginnerDeep learning4.0(3)53 lessonsSample
Mira Okafor$5
AI Strategy Basics for Executives

AI Strategy Basics for Executives

A clear, hype free grounding in what AI means for your organisation and how to lead the first stepsBeginnerAI for business4.7(3)53 lessonsSample
Sofia BrandtFree
Estimating AI Costs and Returns Honestly

Estimating AI Costs and Returns Honestly

Build cost and benefit estimates with ranges and assumptions you can defend in a budget meetingIntermediateAI for business4.0(3)53 lessonsSample
Sofia Brandt$8
Clinical Literature Triage with AI

Clinical Literature Triage with AI

Screen and summarise clinical research faster with AI, then appraise the evidence that matters yourselfAdvancedAI for professionals4.7(3)53 lessonsSample
Xavier Lindgren$12
Data Analysis Agents for Spreadsheets and SQL

Data Analysis Agents for Spreadsheets and SQL

Use or build agents that query data, run analysis and explain results you can actually verifyIntermediateAI agents4.3(3)53 lessonsSample
Jamal Haddad$8
Embeddings Explained for Builders

Embeddings Explained for Builders

Understand what embeddings capture, what they miss and how to use them for search, grouping and matching.BeginnerRAG and search4.5(2)53 lessonsSample
Emeka Nwosu$4
Training a Style or Subject Adapter

Training a Style or Subject Adapter

Curate data, train a small adapter and test it honestly for a style or subjectAdvancedImage and video AI4.7(3)53 lessonsSample
Quentin Adebayo$12
Probability for Machine Learning

Probability for Machine Learning

Use random variables, conditional probability and distributions the way ML models doIntermediateMath for AI4.3(3)53 lessonsSample
Kenta Arai$7
Rate Limits, Retries and Backoff

Rate Limits, Retries and Backoff

Handle 429s and overloads gracefully with backoff, jitter, client side pacing and retries that never cause storms.IntermediateBuilding with LLM APIs4.7(3)53 lessonsSample
Farid Haddad$7
Build Your First Eval Set

Build Your First Eval Set

Create a small, honest set of test cases for your LLM feature and use it to judge every change.BeginnerEvaluation and testing4.7(3)52 lessonsSample
Gonzalo IbarraFree
Embeddings: meaning as numbers

Embeddings: meaning as numbers

See how words and documents become vectors, and why similar meanings end up close togetherIntermediateHow language models work4.7(3)52 lessonsSample
Bastian Weber$6