From Hello World to Autonomous Production Systems. Master the full agent lifecycle — design, build, protect, observe, and deploy — with hands-on code in Python and TypeScript.
The appendices fill in language and framework background that the modules assume you already have — Appendix A is the de facto prerequisite for M01, so start there if venv, pip, or JSON are unfamiliar. The bonus pages are genuinely optional and go wider than the course needs. If you have never used an AI coding tool on a real codebase, take Code With AI before this course.
Three curated paths through the curriculum based on your goals and available time.
Preparing for the Claude Certified Architect exam? Track 9 (M25–M27B) layers on top of any path.
5 progressive capstones across 3 industry domains, plus 1 bonus lab and a 3-domain graduation project (Capstone 7). Pick one domain and follow it through all five levels, or mix and match.
Build the same agent three times: once with the raw API loop, once with claude-agent-sdk, and once spec-driven via Claude Code. Compare code size, dev time, flexibility, and control across all three. The capstone version of M00B.
Migrate a legacy Oracle database to PostgreSQL 16 — schema, data, PL/SQL and application SQL — against two live containers. A coordinator plus five specialists, a read-only source enforced in code, a validator that proves its own work, and a cutover gate only a human can open. Then Capstone 8B rebuilds the identical problem with Agent Skills instead of subagents, and measures which architecture actually did better.
Module dependencies — complete prerequisites before moving on.
📂 The labs and sample projects for this course live in github.com/varasrinivas/agenticai-course — git clone https://github.com/varasrinivas/agenticai-course.git