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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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149 tutors

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CI and testing for ML projects

CI and testing for ML projects

Add fast automated checks that catch broken data, code and models before they reach usersIntermediateEvaluation and testingNewMalik Brennan$8 Exploratory Data Analysis Step by Step

Exploratory Data Analysis Step by Step

Explore a new dataset with a clear routine and turn what you notice into testable questionsBeginnerData science and statisticsNewLin Zhao$4 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 Gradient Descent by Hand

Gradient Descent by Hand

Take gradient descent steps with a pencil and feel how learning rates make or break trainingBeginnerMath for AINewLeandro Ferraz$4 Hyperparameter Tuning on a Budget

Hyperparameter Tuning on a Budget

Search smarter, spend less compute and avoid overfitting your validation setAdvancedMachine learningNewLukas Brenner$11 Distributions in the Wild

Distributions in the Wild

Recognise the common distributions in real data and know what each impliesBeginnerData science and statisticsNewLina Khoury$4 Overfitting and Regularisation

Overfitting and Regularisation

Diagnose overfitting with learning curves and fix it with the right kind of regularisationIntermediateMachine learningNewLukas Brenner$6 Monte Carlo Simulation for Intuition

Monte Carlo Simulation for Intuition

Answer tricky probability and planning questions by simulating them thousands of timesBeginnerData science and statisticsNewKenta Arai$4 Information Theory and Cross Entropy

Information Theory and Cross Entropy

Understand entropy, cross entropy, KL divergence and perplexity from first principlesAdvancedMath for AINewKenta Arai$11 Evaluating generated text

Evaluating generated text

Measure the quality of generated text with metrics, people and model judges, and know each one's limitsIntermediateEvaluation and testingNewMateo Rojas$8 Self supervised and contrastive learning

Self supervised and contrastive learning

Learn how models build useful representations from unlabelled data, and how to test themAdvancedComputer visionNewMateo Rojas$11 Bayesian Thinking for Analysts

Bayesian Thinking for Analysts

Update beliefs with data using priors, likelihoods and posteriors you can explainIntermediateData science and statisticsNewLina Khoury$7