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

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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

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Which Maths Do You Need for ML?

Which Maths Do You Need for ML?

Build a realistic maths study plan matched to the kind of AI work you want to doAll levelsMath for AI4.3(3)36 lessonsSampleLeandro Ferraz$5 Deciding When a Product Needs AI

Deciding When a Product Needs AI

Judge whether an AI feature solves a real user problem before your team builds itIntermediateAI for product and operations4.7(3)36 lessonsSampleSanjana Rao$8 Images and Documents as Model Input

Images and Documents as Model Input

Send photos, screenshots, charts and PDFs to a model and get answers you can check and trust.BeginnerBuilding with LLM APIs4.5(2)36 lessonsSampleGreta Lindqvist$5 How we got here: a short history of AI

How we got here: a short history of AI

Follow AI from rule based programs to today's chatbots and see why progress came in wavesBeginnerAI basics4.5(2)36 lessonsSampleAmara Okafor$4 Extracting Structured Data from Messy Text

Extracting Structured Data from Messy Text

Pull reliable fields out of emails, notes and forms into clean records you can sort, count and trustIntermediateAI automation4.5(2)36 lessonsSampleHamza Qureshi$7 Error Handling and Exception Queues in Automations

Error Handling and Exception Queues in Automations

Design automations that retry sensibly, park problems in a queue and never fail silentlyIntermediateAI automation4.5(2)36 lessonsSampleHamza Qureshi$8 Parsing PDFs and Messy Documents

Parsing PDFs and Messy Documents

Get clean, well ordered text, tables and page numbers out of PDFs, scans, slides and office files.BeginnerRAG and search4.5(2)36 lessonsSampleFumiko Arai$5 Auditing a model for bias: a hands-on method

Auditing a model for bias: a hands-on method

Run a structured fairness audit with clear metrics, subgroup tests and an honest written reportAdvancedAI safety and ethics4.5(2)36 lessonsSampleAisha Rahman$11 Jailbreaks, prompt injection and model misuse

Jailbreaks, prompt injection and model misuse

Understand how AI systems are manipulated and the defensive design that limits the damageIntermediateAI safety and ethics4.5(2)36 lessonsSampleBao Tran$7 Sampling and Bias in Samples

Sampling and Bias in Samples

Judge whether a sample can speak for a population, and why bigger is not always betterBeginnerData science and statistics4.5(2)35 lessonsSampleLina Khoury$4 Ad Images: Testing Visual Variants

Ad Images: Testing Visual Variants

Make ad image variants that test one idea at a time and learn from the resultsIntermediateAI for design4.5(2)35 lessonsSampleRohan Mehta$6 Reranking Retrieved Results

Reranking Retrieved Results

Add a reranking stage that puts the truly relevant passages first, within your latency and cost budget.AdvancedRAG and search4.5(2)35 lessonsSampleEmeka Nwosu$10