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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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Data Science Interview Preparation

Data Science Interview Preparation

Prepare for SQL, statistics, experimentation, product sense and case rounds with realistic practiceAdvancedAI careers4.7(3)59 lessonsSampleYohannes Tesfaye$12 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 lessonsSampleNeha VaradanFree 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 lessonsSampleKojo Amankwah$8 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 lessonsSampleKatarzyna 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 lessonsSampleLin Zhao$6 Anomaly Detection in Practice

Anomaly Detection in Practice

Find unusual events in data without drowning your team in false alarmsAdvancedMachine learning4.7(3)51 lessonsSampleKenta Arai$10 Incident response for ML systems

Incident response for ML systems

Detect, contain and learn from ML failures, from silent quality drops to harmful outputsAll levelsMLOps and deployment4.7(3)51 lessonsSampleMalik Brennan$7 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 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 How language models are pretrained

How language models are pretrained

Understand the data, objective, scaling and stability work behind large language model pretrainingAdvancedDeep learning4.7(3)45 lessonsSampleMateo Rojas$13 Diffusion models from noise to sample

Diffusion models from noise to sample

Understand how diffusion models learn to remove noise and how guidance and latents shape the resultAdvancedDeep learning4.7(3)44 lessonsSampleMateo Rojas$12 Data Leakage Detective

Data Leakage Detective

Find the hidden leaks that make models look brilliant in testing and fail in productionAdvancedMachine learning4.7(3)43 lessonsSampleLukas Brenner$10