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

Find a tutor

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

Filters

Clear
Fine tune, prompt or retrieve?

Fine tune, prompt or retrieve?

Choose between prompting, retrieval and fine tuning for your problem, and know whyAll levelsFine tuning and training4.7(3)59 lessonsSample
Neha VaradanFree
Sentiment analysis done carefully

Sentiment analysis done carefully

Measure opinions in text without fooling yourself about sarcasm, mixed views or skewed averagesBeginnerNLP4.3(3)59 lessonsSample
Nadia Haddad$4
Expected Value and Variance, Gently

Expected Value and Variance, Gently

Understand averages of uncertain outcomes and how much they spread, with dice, games and decisionsBeginnerMath for AI4.3(3)58 lessonsSample
Kenta Arai$4
Experiment tracking you will actually use

Experiment tracking you will actually use

Log runs so you can compare, reproduce and explain results months later, with any toolBeginnerMLOps and deployment4.3(3)58 lessonsSample
Malik Brennan$4
Naive Bayes Classifiers

Naive Bayes Classifiers

Build a fast text classifier from counts and Bayes rule, and know its blind spotsBeginnerMachine learning4.0(3)58 lessonsSample
Kavya Raman$3
Data Science Interview Practice

Data Science Interview Practice

Practise statistics, ML, SQL and case questions with structured feedback on your answersAll levelsData science and statistics4.3(3)57 lessonsSample
Kojo Amankwah$8
Convolutional networks from the pixel up

Convolutional networks from the pixel up

See how convolutions turn pixels into features, and calculate shapes and parameters yourselfBeginnerComputer vision4.7(3)56 lessonsSample
Nikolai Sorin$5
Tokenisation: how text becomes numbers

Tokenisation: how text becomes numbers

See how models split text into tokens, why it matters for cost and context, and where it trips upBeginnerHow language models work4.7(3)56 lessonsSample
Nadia HaddadFree
GPUs and AI hardware for beginners

GPUs and AI hardware for beginners

Understand what GPUs do for AI and estimate whether a model will fit on your hardwareBeginnerMLOps and deployment4.7(3)55 lessonsSample
Magnus EriksenFree
Reading Maths Notation in AI Papers

Reading Maths Notation in AI Papers

Translate the symbols in machine learning papers into plain words and small examplesAll levelsMath for AI4.7(3)55 lessonsSample
Katarzyna Wolska$6
Metric Definitions That Hold Up

Metric Definitions That Hold Up

Define metrics precisely so every dashboard and team means the same thingAll levelsData science and statistics4.3(3)54 lessonsSample
Lin Zhao$6
Speech to text pipelines

Speech to text pipelines

Turn recordings into accurate, timestamped transcripts and understand where speech recognition failsBeginnerAudio and voice AI4.7(3)54 lessonsSample
Nadia Haddad$5