Master Agentic AI Within 2Hours-From Zero To Pro Master

About this course

Everyone is talking about AI agents. But what is an agent, really? And how do you build one?

This course answers both questions in about two hours. Every idea is explained in simple English, with a diagram, and then shown in working Python code. Every code demo in this course was run, and you see the real output.

Part 1: Foundations- What "agentic" means, and how an agent differs from a chatbot.- The agent loop: think, act, observe, repeat.- When you should use a simple workflow instead of an agent.

Part 2: The LLM inside the agent- Tokens, context window and effort, in four minutes.- System prompts and roles.- Structured output: make the model reply in clean JSON.Part 3: Build agents in Python- Set up Python and store your API key safely.- Give the agent tools: functions it can call.- Write the agent loop yourself, line by line, and stop infinite loops.- Add memory, RAG (search your own documents), planning and self-reflection.

Part 4: Multi-agent systems and frameworks- Multi-agent patterns: sequential, manager-worker and parallel.- Build a researcher agent and a writer agent that work together.- A clear tour of the popular frameworks and MCP, so you know what to learn next.

Part 5: Production and capstone- Guardrails, prompt injection and human approval.- Testing, monitoring and controlling cost.- Capstone: build a customer-support agent for BrightCart, a fictional online shop.

All demos use a fictional shop and sample data. Each lesson has a quiz, the code files and a downloadable PDF guide.## Learning objectives (8)1. Explain what an AI agent is and how it differs from a chatbot and from a fixed workflow.2. Describe the agent loop and the ReAct pattern of reasoning and acting.3.

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