Free course material
Move from agent demos to bounded capability.
AI Agents
Understand agent loops, tools, memory, orchestration, evaluation, and the safety boundaries that make agents useful in real work.
What this course is about
A practical path from understanding to application.
This course turns agent enthusiasm into practical system design. Learners explore when a workflow is enough, when an agent is justified, how tools and memory change the risk profile, and how to evaluate the complete trajectory rather than only the final answer.
Covered material
What learners will work through.
- Agent foundations: loops, goals, state, tools, memory, and control flow
- Workflows versus agents and choosing the least autonomous system that works
- Tool design, permissions, orchestration, delegation, and interoperability
- Planning, reflection, multi-agent patterns, and human-in-the-loop boundaries
- Trajectory evaluation, tracing, observability, cost, latency, and failure analysis
- Security, prompt injection, data boundaries, escalation, and production readiness
Who it is for
Meet learners where they are.
Engineers, solution architects, product leaders, researchers, and teams deciding how to introduce agentic workflows without losing control, explainability, or operational discipline.
Adapt this course
Bring the material to your organization.
We can adapt the level, examples, exercises, and pace for executives, non-technical groups, technical teams, or mixed audiences. Sessions combine theory with practical and coding work where it fits, led by educators who meet with your group.
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GenAI & agent development
Connect open learning with the strategy, delivery, and adoption support around it.