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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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Computer vision Clear all

Object detection explained

Object detection explained

Understand boxes, IoU, NMS and mAP well enough to train, evaluate and debug a detectorIntermediateComputer vision4.7(3)75 lessonsSampleNoor Siddiqui$8 Image embeddings and visual search

Image embeddings and visual search

Build image similarity and text to image search, and measure whether results are actually relevantIntermediateComputer vision4.7(3)71 lessonsSampleNoor Siddiqui$7 Image classification, first principles

Image classification, first principles

Plan, train and honestly evaluate an image classifier, from defining classes to studying its mistakesBeginnerComputer vision4.7(3)64 lessonsSampleNoor SiddiquiFree Vision language models: what they see

Vision language models: what they see

Know how AI models read images, what they get right and wrong, and how to check their answersAll levelsComputer vision4.7(3)61 lessonsSampleNoor Siddiqui$6 Convolutional networks from the pixel up

Convolutional networks from the pixel up

See how convolutions turn pixels into features, and calculate shapes and parameters yourselfBeginnerComputer vision4.7(3)56 lessonsSampleNikolai Sorin$5 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 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 Data augmentation for vision

Data augmentation for vision

Choose image augmentations that reflect real variation, keep labels correct and improve generalisationBeginnerComputer vision4.0(3)44 lessonsSampleNoor Siddiqui$4 Image segmentation: semantic, instance, panoptic

Image segmentation: semantic, instance, panoptic

Label every pixel correctly: understand the three kinds of segmentation, their models and metricsIntermediateComputer vision4.3(3)40 lessonsSampleNoor Siddiqui$8 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 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