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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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Personalisation With Privacy in Mind

Personalisation With Privacy in Mind

Design personalised marketing and sales messages that customers find useful, not unsettlingAdvancedAI for marketing and sales4.3(3)62 lessonsSampleSantiago Ferreira$12 Open versus closed models, explained fairly

Open versus closed models, explained fairly

Understand open weights, open source and closed APIs, and how to choose between themAll levelsHow language models work4.3(3)62 lessonsSampleBenedict Asante$5 Music Generation and Its Copyright Questions

Music Generation and Its Copyright Questions

Make music with AI tools and understand the rights, licences and risks in plain termsAll levelsAudio and voice AI4.0(3)61 lessonsSamplePavel Novak$4 Vision language models: what they see

Vision language models: what they see

Know how AI models read images, what they get right and wrong, and how to check their answersAll levelsComputer vision4.7(3)61 lessonsSampleNoor Siddiqui$6 Preference tuning: RLHF, DPO and related methods

Preference tuning: RLHF, DPO and related methods

Understand how models are tuned on human preferences, from reward models to direct preference lossesAdvancedFine tuning and training4.7(3)60 lessonsSampleNeha Varadan$14 Model Graded Evals and Their Pitfalls

Model Graded Evals and Their Pitfalls

Use language models as graders without fooling yourself: biases, validation against people and safeguards.AdvancedEvaluation and testing4.3(4)60 lessonsSampleGonzalo Ibarra$11 The transformer, block by block

The transformer, block by block

Trace a token through every part of a transformer and count where the parameters liveAdvancedDeep learning4.7(3)60 lessonsSampleNikolai Sorin$12 Choosing the Right Model for a Task

Choosing the Right Model for a Task

Pick a model by testing it on your own task, weighing quality, speed, cost, context and data handling.All levelsBuilding with LLM APIs4.3(3)60 lessonsSampleGabriela Sousa$5 Ad Copy and Creative Testing With AI

Ad Copy and Creative Testing With AI

Generate ad angles with AI, then test them with designs that can tell signal from noiseAdvancedAI for marketing and sales4.3(4)60 lessonsSampleThea Lindqvist$11 Studying with Dyslexia or ADHD Using AI Tools

Studying with Dyslexia or ADHD Using AI Tools

Use AI for reading, planning and focus support that fits how your brain works, within your course rulesAll levelsAI for education4.7(3)60 lessonsSampleWanjiru Kamau$5 Fallbacks for Provider Outages and Errors

Fallbacks for Provider Outages and Errors

Keep LLM features working through outages, overloads and slowdowns with deadlines, breakers and fallbacks.AdvancedBuilding with LLM APIs4.7(3)60 lessonsSampleFarid Haddad$11 Gradient Boosting for Tabular Data

Gradient Boosting for Tabular Data

Understand, tune and debug boosted trees, the workhorse of structured data problemsAdvancedMachine learning4.7(3)60 lessonsSampleKavya Raman$12