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

64 tutors

All Machine learning Intermediate Clear all

Backpropagation in practice

Backpropagation in practice

Follow gradients through a real network and fix the training bugs that come from misusing themIntermediateDeep learning4.5(4)91 lessonsSampleMira Okafor$7 Imbalanced Classes, Handled Carefully

Imbalanced Classes, Handled Carefully

Model rare events like fraud or failures without tricks that quietly backfireIntermediateMachine learning4.5(4)86 lessonsSampleLukas Brenner$7 Communicating Results to Non Experts

Communicating Results to Non Experts

Turn analysis into clear sentences, simple charts and decisions people act onAll levelsData science and statistics4.3(4)82 lessonsSampleKojo Amankwah$5 Named entity recognition in practice

Named entity recognition in practice

Extract people, places, organisations and custom entities from text, and evaluate the results properlyIntermediateNLP4.7(3)79 lessonsSampleNadia Haddad$7 Instruction tuning a base model

Instruction tuning a base model

Turn a base model that only continues text into one that follows instructions in a reliable formatIntermediateFine tuning and training4.0(3)75 lessonsSampleNeha Varadan$9 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 Which Model When: Choosing an Algorithm

Which Model When: Choosing an Algorithm

Pick a sensible model family for your data, constraints and goals, then test it fairlyAll levelsMachine learning4.3(3)74 lessonsSampleKenta Arai$7 Machine translation: how it works and fails

Machine translation: how it works and fails

Understand how machines translate, judge translation quality and know when a human translator is neededAll levelsNLP4.3(3)74 lessonsSampleNadia Haddad$6 End to End Tabular ML Project

End to End Tabular ML Project

Take one tabular dataset from question to tested model to clear write upAll levelsData science and statistics4.3(4)72 lessonsSampleLukas Brenner$9 Feature Engineering for Tabular Data

Feature Engineering for Tabular Data

Create features that help models learn, without leaking the answerIntermediateMachine learning4.3(3)72 lessonsSampleLin Zhao$7 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 Attention mechanisms, step by step

Attention mechanisms, step by step

Compute attention by hand, then understand masks, heads, KV caching and efficient variantsIntermediateDeep learning4.3(4)66 lessonsSampleNikolai Sorin$8