Beginner’s Guide to Agentic AI Micro-Credential

Beginner’s Guide to Agentic AI Micro-Credential

Duration: 3-4 Hours

Description

A chatbot answers a question; an agent decides what to do about it. This session introduces the distinction that matters most in AI right now — the agent loop of perceiving a situation, reasoning about it, and taking action — and builds it up piece by piece: planning, tool use, and mapping a real task onto a workflow an agent can actually execute. In guided labs, participants build a simple fact-finding agent from scratch, connect it to an external tool using the Model Context Protocol (MCP) — the emerging standard most major AI platforms now support — add memory so it doesn’t lose context between steps, and implement basic guardrails so it fails safely instead of confidently doing the wrong thing.

Audience

This session is a genuine starting point — built for professionals, students, and technically curious learners with no prior agent-building experience. Some comfort following structured, step-by-step instructions is helpful, but deep programming experience is not required to complete the labs. It’s the right first stop for anyone who keeps hearing “agentic AI” and wants to actually build one before deciding whether to go deeper.

Objectives

  • Define what an AI agent is and how it differs from a simple LLM application
  • Understand the core components of an AI agent: perception, planning, and action
  • Build a simple agent that uses a tool, including an MCP-connected tool, to complete a task
  • Debug and evaluate a basic agent’s behavior

Prerequisites

Familiarity with basic programming concepts (such as variables, loops, and functions) and comfort working in a modern programming environment (e.g., Python) will help participants follow the labs more easily, but these skills are not mandatory. A general understanding of AI or machine learning concepts is helpful but not essential.

Related AI Courses

See the full AI training roadmap and course directory for how this fits into a broader learning path.

Ready to go further? See Building Multi-Agent Systems Micro-Credential for the next step up, the full Introduction to AI Agents course, and eventually Advanced AI Agents for production-grade, multi-agent systems. New to generative AI concepts first? See Beginner’s Guide to Generative AI Micro-Credential.

Course Outline

Module 1: Agentic AI Fundamentals

  • What is an AI Agent?
  • The Agent Loop
  • Key Components – Perception, Reasoning/Planning, and Action/Tool Use
  • Lab – Analyze and Map a Simple Human Task to the Agent Loop

Module 2: Building Your First Agent

  • Introducing a Framework
  • Giving the Agent a Brain
  • Giving the Agent Tools, Including MCP-Connected Tools
  • Lab – Build a Simple Fact-Finder Agent

Module 3: Beyond the Basics

  • Adding Memory
  • Debugging and Evaluation
  • The Importance of Guardrails
  • Next Steps: Multi-Agent Systems