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

28 tutors

Deep learning Clear all

Neurons and layers, built up by hand

Neurons and layers, built up by hand

Compute a small neural network on paper so every layer, weight and shape makes senseBeginnerDeep learning4.7(3)46 lessonsSampleMira Okafor$4 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 Autoencoders and latent spaces

Autoencoders and latent spaces

Learn how networks compress data into a small code and rebuild it, and what that code is good forBeginnerDeep learning4.5(2)44 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 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 Reinforcement learning basics

Reinforcement learning basics

Understand agents, rewards and policies, and compute a Q learning update yourselfBeginnerDeep learning4.7(3)41 lessonsSampleNikolai SorinFree RNNs, LSTMs and why transformers took over

RNNs, LSTMs and why transformers took over

Understand recurrent networks, their gates and limits, and the real reasons attention replaced themIntermediateDeep learning4.5(2)32 lessonsSampleNikolai Sorin$7 Initialisation and normalisation layers

Initialisation and normalisation layers

Understand how weight initialisation and normalisation keep deep networks trainableAdvancedDeep learningNewMira Okafor$11 Positional information in transformers

Positional information in transformers

Learn how transformers know word order, from sinusoids to rotary embeddings and long context limitsIntermediateDeep learningNewNikolai Sorin$8 Writing your first training loop

Writing your first training loop

Write a clear, correct training loop in any framework and know what each line is forBeginnerDeep learningNewMira Okafor$4 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