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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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Foundations 89

All Foundations89 AI basics25 How language models work23 AI safety and ethics49

Everyday AI 91

All Everyday AI91 Prompting20 ChatGPT and Claude at work25 AI for writing29 AI for research and study33

Building with AI 162

All Building with AI162 Python for AI21 Building with LLM APIs30 RAG and search21 Evaluation and testing21 AI agents31 AI automation25 AI coding assistants30

Machine learning 149

All Machine learning149 Machine learning35 Data science and statistics30 Math for AI23 Deep learning28 NLP14 Computer vision14 Fine tuning and training12 MLOps and deployment18

Creative AI 77

All Creative AI77 Image and video AI58 Audio and voice AI12 AI for design33

AI at work 145

All AI at work145 AI for business34 AI for marketing and sales23 AI for product and operations28 AI for education28 AI for professionals29 AI careers18

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Evaluation and testing Clear all

Evaluating Retrieval Quality

Evaluating Retrieval Quality

Measure whether your retrieval finds the right passages with real queries, relevance labels and the right metrics.AdvancedEvaluation and testing4.7(3)75 lessonsSampleFumiko Arai$11 Evaluating an AI Feature Before Launch

Evaluating an AI Feature Before Launch

Build an evaluation set, grade outputs reliably and set launch gates your team agrees onAdvancedAI for product and operations4.7(3)70 lessonsSampleSanjana Rao$14 Reviewing AI Support Answers for Quality

Reviewing AI Support Answers for Quality

Build a sampling and rubric process to judge AI support answers and catch failures earlyAdvancedAI for product and operations4.7(3)67 lessonsSampleTariq Haddad$12 Evaluating a model after fine tuning

Evaluating a model after fine tuning

Prove a tuned model is actually better, on your task and everywhere else it mattersIntermediateEvaluation and testing4.7(3)65 lessonsSampleNeha Varadan$8 Logging and Tracing LLM Calls

Logging and Tracing LLM Calls

Record every model call and pipeline step so you can explain cost, slowness and bad answers.IntermediateBuilding with LLM APIs4.0(3)65 lessonsSampleFarid Haddad$8 Unit Tests for Python AI Code

Unit Tests for Python AI Code

Test the deterministic parts of LLM apps properly, with fake model clients instead of flaky live calls.IntermediateEvaluation and testing4.3(3)61 lessonsSampleFelix Brandt$6 Model Graded Evals and Their Pitfalls

Model Graded Evals and Their Pitfalls

Use language models as graders without fooling yourself: biases, validation against people and safeguards.AdvancedEvaluation and testing4.3(4)60 lessonsSampleGonzalo Ibarra$11 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 lessonsSampleGonzalo IbarraFree Cost and Latency Budgets for LLM Features

Cost and Latency Budgets for LLM Features

Set cost and speed targets for an LLM feature, measure them honestly and trade them against quality.All levelsBuilding with LLM APIs4.5(2)52 lessonsSampleFarid Haddad$8 Red Teaming and Prompt Injection Testing

Red Teaming and Prompt Injection Testing

Test your LLM app against jailbreaks, prompt injection and data leaks with a repeatable attack suite.AdvancedEvaluation and testing4.7(3)49 lessonsSampleGonzalo Ibarra$12 Rubric Grading for Open Ended Output

Rubric Grading for Open Ended Output

Design rubrics that make grading emails, summaries and explanations consistent, fair and repeatable.IntermediateEvaluation and testing4.3(3)49 lessonsSampleGonzalo Ibarra$6 Measuring Hallucination in LLM Apps

Measuring Hallucination in LLM Apps

Measure how often your app states unsupported things, with claim level checks you can repeat and trust.IntermediateEvaluation and testing4.5(2)42 lessonsSampleGonzalo Ibarra$8