Skip to content

SamplePreview build: teacher profiles, ratings, reviews and lesson counts are sample data.

Log in Find a tutor

Find a tutor

657 tutors in 31 topics, built by 75 teachers. Each one follows a lesson plan its teacher wrote.

Filters

Sort by

Price

Any price Free Paid

Level

Any level Beginner Intermediate Advanced

Topic

All topics

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

Clear

11 tutors

Deep learning Advanced Clear all

Debugging neural network training

Debugging neural network training

A systematic method for finding why a model will not train, diverges or quietly underperformsAdvancedDeep learning4.5(4)66 lessonsSampleNikolai Sorin$10 The transformer, block by block

The transformer, block by block

Trace a token through every part of a transformer and count where the parameters liveAdvancedDeep learning4.7(3)60 lessonsSampleNikolai Sorin$12 How language models are pretrained

How language models are pretrained

Understand the data, objective, scaling and stability work behind large language model pretrainingAdvancedDeep learning4.7(3)45 lessonsSampleMateo Rojas$13 Diffusion models from noise to sample

Diffusion models from noise to sample

Understand how diffusion models learn to remove noise and how guidance and latents shape the resultAdvancedDeep learning4.7(3)44 lessonsSampleMateo Rojas$12 How to read a deep learning paper

How to read a deep learning paper

Read papers in passes, find the real claim and judge the evidence behind itAll levelsAI for research and study4.7(3)41 lessonsSampleNikolai Sorin$6 Initialisation and normalisation layers

Initialisation and normalisation layers

Understand how weight initialisation and normalisation keep deep networks trainableAdvancedDeep learningNewMira Okafor$11 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 Graph neural networks

Graph neural networks

Learn message passing on graphs and build models for nodes, edges and whole graphs without leakageAdvancedDeep learningNewNikolai Sorin$11 Vision transformers in depth

Vision transformers in depth

Understand patch tokens, position embeddings, data needs and compute trade offs in vision transformersAdvancedComputer visionNewNoor Siddiqui$12 Catastrophic forgetting and how to limit it

Catastrophic forgetting and how to limit it

Measure what a model loses when you fine tune it, and use replay, regularisation and merging to limit itAdvancedDeep learningNewNeha Varadan$12 Knowledge distillation: teaching a smaller model

Knowledge distillation: teaching a smaller model

Train compact student models from large teachers with soft targets, generated data and careful evaluationAdvancedDeep learningNewMagnus Eriksen$12