Learning Tracks
9 tracks, 96 modules published. Start anywhere: or find the path for your role .
Track 1
Foundations
How LLMs work, what they can and can't do, and the concepts that everything else builds on.
Track 2
Retrieval-Augmented Generation
Connecting LLMs to your own data — from basic pipelines to advanced retrieval architectures.
Track 3
Protocols & Integration
MCP, A2A, AG-UI — the standards that let AI systems communicate, delegate, and interoperate.
Track 4
Agent Architecture
Building multi-agent systems that work reliably — orchestration, failure modes, and production patterns.
Track 5
Infrastructure & Serving
Running AI workloads reliably and cost-efficiently — from local models to production serving.
Track 6
Evaluation & Observability
How to know if your AI system is working — evals, tracing, cost management, and CI/CD gates.
Track 7
Safety & Compliance
Prompt injection, supply chain risk, guardrails, EU AI Act — what you need to ship responsibly.
Track 8
Strategy & Business
ROI, buy vs build, team structure, AI economics — the decisions that matter at the org level.
Track 9
Multimodal AI
Systems that see, hear, and act — vision models, audio AI, and multimodal safety.