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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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Metric Definitions That Hold Up

Metric Definitions That Hold Up

Define metrics precisely so every dashboard and team means the same thingAll levelsData science and statistics4.3(3)54 lessonsSampleLin Zhao$6 Random Forests and Bagging

Random Forests and Bagging

Understand why averaging many trees works and how to tune a forest sensiblyIntermediateMachine learning4.3(3)54 lessonsSampleKavya Raman$6 Speech to text pipelines

Speech to text pipelines

Turn recordings into accurate, timestamped transcripts and understand where speech recognition failsBeginnerAudio and voice AI4.7(3)54 lessonsSampleNadia Haddad$5 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 lessonsSampleMira Okafor$5 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 lessonsSampleKenta Arai$7 The Chain Rule and Backpropagation

The Chain Rule and Backpropagation

Compute gradients through a network by hand and see exactly what backpropagation doesIntermediateMath for AI4.7(3)52 lessonsSampleLeandro Ferraz$7 Anomaly Detection in Practice

Anomaly Detection in Practice

Find unusual events in data without drowning your team in false alarmsAdvancedMachine learning4.7(3)51 lessonsSampleKenta Arai$10 Incident response for ML systems

Incident response for ML systems

Detect, contain and learn from ML failures, from silent quality drops to harmful outputsAll levelsMLOps and deployment4.7(3)51 lessonsSampleMalik Brennan$7 OCR and document understanding

OCR and document understanding

Understand how machines read scans, forms and tables, and how to check that they read correctlyBeginnerComputer vision4.3(3)51 lessonsSampleNoor Siddiqui$5 GANs: generator versus discriminator

GANs: generator versus discriminator

Understand how adversarial training works, why it is unstable and where GANs still make senseIntermediateDeep learning4.0(3)50 lessonsSampleMateo Rojas$8 Transfer learning with pretrained models

Transfer learning with pretrained models

Get strong results from small datasets by starting with a model that has already learnedBeginnerComputer vision4.7(3)50 lessonsSampleMateo Rojas$5 Activation functions explained

Activation functions explained

Learn what ReLU, sigmoid, tanh, GELU and softmax do, and choose the right one for each layerBeginnerDeep learning4.5(2)50 lessonsSampleMira Okafor$4