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

149 tutors

All Machine learning Clear all

Overfitting, regularisation and dropout

Overfitting, regularisation and dropout

Recognise overfitting from your curves and pick the right fix, from more data to dropoutBeginnerDeep learning4.7(3)50 lessonsSampleMira Okafor$5 Fairness Checks for ML Models

Fairness Checks for ML Models

Measure how a model treats different groups and understand the trade offs between fairness metricsIntermediateMachine learning4.7(3)50 lessonsSampleKojo Amankwah$7 From Spreadsheets to Data Analysis

From Spreadsheets to Data Analysis

Bring your spreadsheet skills into structured, repeatable data analysisBeginnerData science and statistics4.3(3)50 lessonsSampleLin Zhao$3 Optimisation Basics for ML

Optimisation Basics for ML

Understand momentum, adaptive methods, schedules and the shape of loss landscapesAdvancedMath for AI4.7(3)50 lessonsSampleLeandro Ferraz$11 Matrix Multiplication Intuition

Matrix Multiplication Intuition

See matrix multiplication as many dot products and as a transformation of spaceBeginnerMath for AI4.7(3)50 lessonsSampleKatarzyna Wolska$5 Loss Functions and What They Reward

Loss Functions and What They Reward

Choose a loss that matches what you actually care about, and know what each one optimisesIntermediateMachine learning4.3(3)50 lessonsSampleLeandro Ferraz$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 Data Cleaning Fundamentals

Data Cleaning Fundamentals

Turn a messy table into data you can trust, with every change written downBeginnerData science and statistics4.7(3)49 lessonsSampleLin Zhao$4 Train, Validation and Test Splits

Train, Validation and Test Splits

Split your data so your model's score means something outside your laptopBeginnerMachine learning4.7(3)48 lessonsSampleLukas BrennerFree Versioning models and data

Versioning models and data

Know exactly which data and code produced every model, and recover or delete them when neededBeginnerMLOps and deployment4.7(3)48 lessonsSampleMalik Brennan$5 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 Summarisation systems and their failure modes

Summarisation systems and their failure modes

Build and judge summaries that stay faithful to the source, from short notes to long reportsAll levelsNLP4.7(3)46 lessonsSampleMateo Rojas$6