Learn AI in a structured path

Models, training, tokens and why AI sometimes makes things up.

• From rules to learning9 min
• How models are trained12 min
• Hallucinations & limits11 min
• Checkpoint quizpass 70%

Speak the language: context windows, embeddings, agents, fine-tuning.

• The vocabulary map14 min
• Context windows in practice13 min
• Embeddings made simple15 min
• Terminology quizpass 70%

Read a pricing page, a model card and a release note without getting lost.

• Tokens, limits and what you pay for13 min
• Reading a model card14 min
• Decoding release notes and benchmarks15 min
• Terminology in practice quizpass 70%

Reusable prompt patterns, structured output, evaluation and iteration.

• Role, task, context, format16 min
• Few-shot and chain prompting18 min
• Structured output & JSON15 min
• Prompt library workshop22 min
• Practitioner quizpass 70%

Wire tools together with Make, n8n and Zapier to remove manual work.

• Mapping a manual process12 min
• Your first AI automation24 min
• Error handling & guardrails19 min
• Automation quizpass 70%

Tool use, planning loops, evaluation, cost control and human handover.

• Agent architectures22 min
• Tools, memory & state25 min
• Evaluating agent quality18 min
• Specialist quizpass 70%

Chunking, embeddings, retrieval quality and grounded answers you can trust.

• Why retrieval beats fine-tuning17 min
• Chunking strategies16 min
• Measuring retrieval quality21 min
• RAG quizpass 70%

Build an AI adoption roadmap, policy, budget and ROI model for a team.

• Opportunity mapping18 min
• AI policy & risk20 min
• Budgeting your AI stack19 min
• Strategist capstonepass 80%

Take an AI feature from idea to shipped: scoping, evals, cost control and launch.

• Scoping an AI feature people want18 min
• Evaluation before launch22 min
• Unit economics of an AI feature20 min
• Shipping, monitoring and iterating17 min
• Product capstonepass 80%