Build Your First AI Agent — No Code

A practical, no-code course on the fastest-growing AI skill: agents. Learn what an AI agent actually is (versus a chatbot or a fixed automation), how it works as an LLM 'brain' plus tools plus a plan-act-check loop, and how to keep it safe with guardrails. You will ground an agent in your own documents (RAG in plain terms) to build an accurate knowledge assistant, then connect an AI to your apps with no-code tools (Zapier, Make, n8n) to build a real working agent that triages and drafts with your approval - and finish with a safe-agent policy and a 90-day roadmap. Every lesson ends with a hands-on lab that produces a real asset: an agent brief, a grounded assistant, a working automation, an ROI scorecard, and a one-page governance policy. Includes concept tables, knowledge checks, mastery checks, a cumulative final exam, a downloadable playbook pack and a spaced-repetition flashcard deck. Vendor-neutral with Claude as the primary example; free, beginner-friendly, no coding.

0.00 USD

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What you'll study

Part 1 — What an AI Agent Really Is

• Assistant, automation, or agent?
• How agents work — and how to keep them safe

Part 2 — Ground It in Your Knowledge

• Why grounding matters (RAG in plain terms)
• Build a knowledge assistant from your material

Part 3 — Agents That Take Action

• Triggers, steps and tools
• Build a working agent workflow

Part 4 — Put It to Work & Keep It Safe

• Make it reliable and worth it
• Govern your agents (the safe-agent policy)

Gold — Agents in Depth: LLM, Chatbot, and the Agent Loop

• LLM, chatbot, agent — telling them apart in practice
• The agent loop — perceive, plan, act, observe

Gold — Under the Hood: Tokens, Context Windows & Temperature

• Tokens, context windows and why agents 'forget'

Gold — Tools & Function-Calling: How Agents Actually Do Things

• Function-calling in plain terms

Gold — Memory: Short-Term, Long-Term & Vector Stores

• Short-term vs long-term memory, and how vector stores work

Gold — Retrieval-Augmented Generation, End to End

• The RAG pipeline and how to debug it

Gold — Designing the System Message & Prompts for Agents

• The agent's job description (system message)

Gold — No-Code Platforms, Integrations, Triggers & APIs

• Wiring agents to your apps without code

Gold — Guardrails, Hallucinations & Handling Failure

• Keeping agents safe when things go wrong

Gold — Human-in-the-Loop, Testing & Evaluating an Agent

• Prove it works before you trust it

Gold — Cost, Latency, Deployment & Monitoring

• Running an agent in the real world

Gold — Multi-Step Workflows & Multi-Agent Basics

• From one agent to a small team of agents

Gold — Real Use Cases: Support, Research, Scheduling, Data Entry

• Four agents you can actually ship

Gold — Ethics, Data Privacy & Responsible Agents

• Using agents responsibly

Practice and exam readiness

• Final Practice Exam
• Expanded Mock Exam
• Spaced-repetition flashcard deck (SM-2) for daily review
• Shareable, verifiable completion certificate

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• Automating Your Work with Claude — Practical AI Automation for Business Users
• The AI-Powered Small Business — Automate, Market & Grow

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