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

8 tutors

MLOps and deployment Intermediate Clear all

Planning the cost of a training run

Planning the cost of a training run

Estimate compute, time, memory and budget for a training or fine tuning run before you spendAll levelsFine tuning and training4.3(3)65 lessonsSampleMagnus Eriksen$7 Monitoring models and catching drift

Monitoring models and catching drift

Notice when a live model starts getting worse, even before the true answers arriveIntermediateMLOps and deployment4.7(3)58 lessonsSampleMalik Brennan$9 Batching and caching for model inference

Batching and caching for model inference

Serve more requests on the same hardware by batching smartly and caching what can be reusedIntermediateMLOps and deployment4.7(3)57 lessonsSampleMagnus Eriksen$9 Incident response for ML systems

Incident response for ML systems

Detect, contain and learn from ML failures, from silent quality drops to harmful outputsAll levelsMLOps and deployment4.7(3)51 lessonsSampleMalik Brennan$7 Quantisation: smaller, faster models

Quantisation: smaller, faster models

Shrink models with lower precision numbers and measure exactly what quality you trade awayIntermediateFine tuning and training4.3(3)49 lessonsSampleMagnus Eriksen$9 Deploying an open weights model

Deploying an open weights model

Choose, size, secure and run an open weights model in production, and compare its real costIntermediateMLOps and deployment4.7(3)46 lessonsSampleMagnus Eriksen$9 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 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