AI & ML · 11 weeks
AI & Machine Learning Developer
AI Agent Engineering & Operations
Operate the agent. Ship the proof. Over eleven weeks you learn to direct working AI agents, debug them when the first output isn’t right, and deploy them under strict guardrails. Every session produces a real artifact, and Demo Day is the assessment.
Get Started →Key Dates & Details
Program Goals
- Learn to direct and operate AI agents rather than just building from scratch
- Debug agent responses, steer output relevance, and catch failure modes
- Implement safety policies, human-in-the-loop workflows, and prompt injection defenses
- Ship real-world artifacts across analytics, sales, support, and multi-agent orchestration
Learning Outcomes
- Master OpenClaw & AI agent architecture
- Debug relevance & instruction execution
- Author safety policies & approval gates
- Build stateful monitoring agents
- Deploy persistent, stack-ready operators
- Ship data-driven decision dashboards
- Automate policy-gated sales outreach
- Build scoped knowledge-base responders
- Orchestrate & harden multi-agent systems
11-Week Course Schedule
System & Memory
Lecture 1: Using AI Agents & Understanding the System (OpenClaw architecture: memory, tools, skills, workflows). Hands-On: Stand up your agent on Discord; run four debugging prompts. Lab 0 + 1: Setup & Debugging Toolkit · Memory → Living Site.
Directing
Lecture 2: Directing, Debugging & Improving AI Agents. Hands-On: Steer the signal; debug relevance, not prose. Lab 2: Daily Briefing Agent.
Safety
Lecture 3: Safety, Guardrails & Real-World Deployment. Hands-On: Chain multi-step workflows; add the first approval gate. Lab 3: Research → Published Asset.
Guardrails
Lab 4: Stateful Monitor + Permission Policy. Build a repeatable monitor that reports only what changed under an authored policy, refusing hidden instructions.
Capstone I
Lab 5: Deploy an AI Agent as a Shared Operator. Build the full stack as a persistent operator—memory, artifacts, workflows, state, guardrails—with a runbook and Demo Day story.
Analytics / Ops
Lab 6: Data → Decision. Ingest a real dataset and ship a live dashboard that leads with the decision, backed by cited numbers.
Sales / Growth
Lab 7: Growth Engine. Research prospects and draft personalized outreach at volume with policy gates and research trails.
Support / Service
Lab 8: Inbound Responder. Answer strictly from a knowledge base and escalate out-of-scope questions immediately.
Orchestration
Lab 9A: Multi-Agent Operation (design & build roles). Stand up individual roles—researcher, drafter, reviewer, publisher—in isolation.
Orchestration
Lab 9B: Multi-Agent Operation (orchestrate & harden). Wire handoffs, introduce QA checks between agents, and add failure recovery mechanisms.
Demo Day
Final: Demo Day assessment. Present your working agent system and artifacts to earn your course certificate.
Capstone Project
The culmination of the course is Demo Day in Week 11. Complete the course and earn a certificate backed by a working, deployed agent system, a portfolio of live artifacts, debugging runbooks, safety guardrails, and documented injection defenses.
Recommended Tools & Technologies
AI Agent framework, OpenClaw architecture (memory, tools, skills, workflows), Discord integrations, stateful monitors, knowledge bases, multi-agent orchestration engines, and prompt injection defense tools.
Enrollment & Next Steps
Show a working agent, not a certificate — then take the certificate too. Contact contact@airobotoedu.com to get started.
Get Started →