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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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Machine learning Clear all

Eigenvalues, Eigenvectors and PCA

Eigenvalues, Eigenvectors and PCA

Derive principal component analysis from eigenvectors and use it with full understandingAdvancedMachine learning4.7(3)39 lessonsSampleKatarzyna Wolska$11 Cross Validation Without Fooling Yourself

Cross Validation Without Fooling Yourself

Use k fold, grouped, time series and nested cross validation correctlyIntermediateMachine learning4.5(2)34 lessonsSampleLukas Brenner$6 Clustering Without Guesswork

Clustering Without Guesswork

Group data with k-means, hierarchical clustering and DBSCAN, and check the groups are usefulBeginnerMachine learning4.7(3)33 lessonsSampleKatarzyna Wolska$4 ML Engineering Interview Preparation

ML Engineering Interview Preparation

Practise ML fundamentals, coding, ML system design and behavioural rounds with realistic mock questionsAdvancedAI careers4.7(3)30 lessonsSampleYohannes Tesfaye$13 Decision Trees You Can Draw

Decision Trees You Can Draw

Build a decision tree by hand and understand every split it makesBeginnerMachine learning4.5(2)22 lessonsSampleKavya Raman$4 Machine learning from zero

Machine learning from zero

The core ideas of machine learning, explained with small, concrete examples.BeginnerMachine learningNewDaniel Reyes$7 Recommender Systems Explained

Recommender Systems Explained

Understand how recommendations are made, evaluated and kept from narrowing what people seeIntermediateMachine learningNewKatarzyna Wolska$8 Hyperparameter Tuning on a Budget

Hyperparameter Tuning on a Budget

Search smarter, spend less compute and avoid overfitting your validation setAdvancedMachine learningNewLukas Brenner$11 Overfitting and Regularisation

Overfitting and Regularisation

Diagnose overfitting with learning curves and fix it with the right kind of regularisationIntermediateMachine learningNewLukas Brenner$6 k Nearest Neighbours, Built by Hand

k Nearest Neighbours, Built by Hand

Predict by similarity and learn why distance, scaling and k decide everythingBeginnerMachine learningNewKavya Raman$3 Logistic Regression for Classification

Logistic Regression for Classification

Model yes or no outcomes, read odds ratios and choose thresholds with intentIntermediateMachine learningNewKavya Raman$6