Build AI Systems That Actually Work
Choose practical courses and hands-on workshops for AI workflows, agents, MCP, and modern agent frameworks—then build, test, and improve systems you can actually use.
No required flagship. Start with the outcome you want and the system you need to build.
Choose the path that matches what you want to build
Courses, workshops, team training, and certification are separated by outcome—so you can buy the path that solves your problem instead of paying for overlapping content.
Core AI Systems
Learn the durable architecture behind useful AI work: inputs, context, state, tools, actions, verification, recovery, and measurable outcomes.
Tools, Protocols & Frameworks
Move from architecture into implementation with focused learning paths for current agent frameworks, protocols, orchestration tools, and developer ecosystems.
Teams & Professional Mastery
Operationalize agent work across a team or demonstrate deeper applied mastery through performance-based learning and assessed decisions.
What do you want AI to do for you?
There is no required first course. Start with the result you want, then choose the learning path built for that job.
AI Workflow Course
Turn recurring tasks into structured, testable AI workflows with controlled inputs, logic, actions, and outcomes.
Explore the course → Build an AI agentAI Agent Course
Design bounded agents around real goals, context, memory, tools, actions, verification, evaluation, and human oversight.
Explore the course → Connect AI to real systemsModel Context Protocol Course
Learn how MCP clients, servers, tools, resources, authorization, security, and reliability fit together.
Explore MCP → Choose the right stackAI Agent Frameworks Course
Compare frameworks by architecture, state, tools, evaluation, observability, deployment, portability, and maintainability.
Compare frameworks →Learn by building inside today’s agent ecosystems
Use durable system principles while getting hands-on with current tools and frameworks. Each workshop is designed around a concrete build—not passive platform tours.
n8n AI Agents
Build agent automations with triggers, tools, APIs, memory, actions, fallbacks, and evaluations.
WorkshopPydanticAI Agents
Build typed Python agents with dependencies, structured outputs, validation, testing, and observability.
WorkshopGoogle ADK Agents
Build, orchestrate, evaluate, observe, and prepare Google ADK agent systems for deployment.
WorkshopLangChain & LangGraph Agents
Build stateful graph-based agents with persistence, tools, human control, tracing, and recovery.
Don’t just finish lessons. Build proof you can apply them.
Applied programs use realistic system decisions, concrete artifacts, transparent criteria, immediate coaching, and revision so learning turns into something you can actually use.
Built for people who want useful skills—not AI theater.
Systems over prompt tricks
Learn inputs, context, state, rules, tools, permissions, actions, verification, recovery, evaluation, and measurable outcomes.
Current tools, durable principles
Tool-specific material is grounded in current platform behavior while the underlying system-design judgment stays portable.
Built around application
Finish with stronger decisions, reusable artifacts, and systems you understand well enough to improve—not just terminology you can repeat.
Train the team. Or prove the skill.
AI Agent Training for Teams
Create shared standards for opportunity selection, permissions, approvals, evaluation, governance, ownership, monitoring, and responsible rollout.
Explore team training →AI Agent Certification
Demonstrate applied agent-design judgment through mastery-based assessments, Decision Labs, stakeholder defense, and a certification portfolio.
Explore certification →Choose the learning path that gets you closer to a working AI system.
Explore the Academy, choose the outcome you want, and start building with a course or workshop designed for real application.