AI & Machine Learning Developer

A 10-week applied program focused on the data and engineering skills needed to build generative AI systems — data pipelines, RAG, function calling, lightweight fine-tuning, AI agents, and end-to-end evaluation.

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

10-Week Course Schedule

• Week 01 — 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.
• Week 02 — Directing: Lecture 2: Directing, Debugging & Improving AI Agents. Hands-On: Steer the signal; debug relevance, not prose. Lab 2: Daily Briefing Agent.
• Week 03 — Safety: Lecture 3: Safety, Guardrails & Real-World Deployment. Hands-On: Chain multi-step workflows; add the first approval gate. Lab 3: Research → Published Asset.
• Week 04 — Guardrails: Lab 4: Stateful Monitor + Permission Policy. Build a repeatable monitor that reports only what changed under an authored policy, refusing hidden instructions.
• Week 05 — 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.
• Week 06 — Analytics / Ops: Lab 6: Data → Decision. Ingest a real dataset and ship a live dashboard that leads with the decision, backed by cited numbers.
• Week 07 — Sales / Growth: Lab 7: Growth Engine. Research prospects and draft personalized outreach at volume with policy gates and research trails.
• Week 08 — Support / Service: Lab 8: Inbound Responder. Answer strictly from a knowledge base and escalate out-of-scope questions immediately.
• Week 09 — Orchestration: Lab 9A: Multi-Agent Operation (design & build roles). Stand up individual roles—researcher, drafter, reviewer, publisher—in isolation.
• Week 10 — Orchestration: Lab 9B: Multi-Agent Operation (orchestrate & harden). Wire handoffs, introduce QA checks between agents, and add failure recovery mechanisms.
• Week 11 — 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.