Chapter D · 4 of 4
Build garage
Code labs & tiny shipping projects
- 01Python only what you need8m
- 1.5Python dictionaries9m
- 1.6Classes and objects10m
- 1.7Python virtual environments9m
- 02Data: tables and simple plots9m
- 2.2NumPy and pandas basics12m
- 2.5File handling9m
- 03Prediction: your first ML idea9m
- 3.5Clustering10m
- 3.7Decision trees10m
- 3.8Random forests10m
- 04Train a tiny model10m
- 4.2Loss functions10m
- 05Neural nets by building10m
- 5.5Deep learning10m
- 06When computers see10m
- 6.5Git basics10m
- 6.6GitHub basics10m
- 07Talk to an LLM from code10m
- 7.25Multimodal API lab10m
- 7.42Local model lab10m
- 7.5Streaming responses9m
- 7.55API errors & retries9m
- 7.58LLM tracing lab10m
- 7.59Cost optimization lab10m
- 7.595Semantic cache lab10m
- 08Build a mini RAG11m
- 8.1Embedding API lab10m
- 8.12Batch API lab10m
- 8.2Vector DB integration lab11m
- 8.22Re-ranking lab10m
- 8.25Fine-tuning lab11m
- 8.45Structured output lab10m
- 8.5Function calling in code11m
- 8.55Agents in code11m
- 8.56Multi-agent in code11m
- 8.57Eval gates in code10m
- 09Tools in code11m
- 9.05Workflow automation in code10m
- 9.15Eval metrics lab10m
- 9.2MCP in code10m
- 9.25Guardrails in code10m
- 9.28Prompt injection in code10m
- 9.35Webhook lab10m
- 9.5Model deployment11m
- 9.55Canary deploy lab10m
- 9.58A/B test lab10m
- 9.59Blue-green deploy lab10m
- 9.7Deploy a RAG app11m
- 9.72RAG quality audit10m
- 9.75Production monitoring lab10m
- 9.8Capstone: support bot with RAG + tools14m
- 9.85Capstone: research bot with citations13m
- 10Capstone: ship a tiny AI app12m
- 10.1Incident response lab10m
- 10.2Runbook lab9m
- 10.3Rate limiting lab10m
- 10.4SLO lab10m
- 10.5Feature flags lab10m
- 10.6Health check lab10m
- 10.7Secrets rotation lab10m
- 10.8Load testing lab10m
- 10.9Disaster recovery lab10m
- 10.91Postmortem lab9m
- 10.92On-call lab9m
- 10.93Capstone ops lab10m
- 10.94Red-teaming lab10m
- 10.95Speech lab10m