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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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MLOps and deployment Beginner Clear all

Planning the cost of a training run

Planning the cost of a training run

Estimate compute, time, memory and budget for a training or fine tuning run before you spendAll levelsFine tuning and training4.3(3)65 lessonsSampleMagnus Eriksen$7 MLOps for a team of one

MLOps for a team of one

Put a model into use responsibly with the few practices that matter when you work aloneBeginnerMLOps and deployment4.7(3)62 lessonsSampleMalik BrennanFree Experiment tracking you will actually use

Experiment tracking you will actually use

Log runs so you can compare, reproduce and explain results months later, with any toolBeginnerMLOps and deployment4.3(3)58 lessonsSampleMalik Brennan$4 GPUs and AI hardware for beginners

GPUs and AI hardware for beginners

Understand what GPUs do for AI and estimate whether a model will fit on your hardwareBeginnerMLOps and deployment4.7(3)55 lessonsSampleMagnus EriksenFree 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 Versioning models and data

Versioning models and data

Know exactly which data and code produced every model, and recover or delete them when neededBeginnerMLOps and deployment4.7(3)48 lessonsSampleMalik Brennan$5 Model cards and ML governance

Model cards and ML governance

Document models honestly and set up light, real governance that helps people make good decisionsBeginnerAI safety and ethics4.0(3)45 lessonsSampleMalik Brennan$5 Wrapping a model in a reliable API

Wrapping a model in a reliable API

Turn a trained model into a small, well behaved web service that fails clearly and safelyBeginnerMLOps and deploymentNewMalik Brennan$5 Medical imaging AI: how it is built and checked

Medical imaging AI: how it is built and checked

Understand how imaging models are trained, validated and overseen, for education onlyAll levelsComputer visionNewMalik Brennan$8 AI visual inspection for factories, explained

AI visual inspection for factories, explained

Learn how camera based defect detection works on a production line, and what makes it succeedBeginnerComputer visionNewMagnus Eriksen$5 On device and edge models

On device and edge models

Decide when a model should run on the phone or device itself, and make it fit and run wellBeginnerMLOps and deploymentNewMagnus Eriksen$6