Overview

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This course introduces beginner learners to the core ideas behind agentic AI using clear language and concrete examples from modern organizations. You will learn how AI agents differ from chatbots, how they use tools and memory, and why enterprises are investing heavily in agent based automation. We will explore high impact use cases in IT support, customer service, sales, operations, and personal productivity from the US, Europe, and fast growing digital markets. You will practice spotting workflows where AI agents can safely assist, using simple opportunity mapping frameworks tailored for non technical professionals. The course also covers essential security, data, and governance considerations in plain language so you can participate confidently in AI conversations at work. By the end, you will be able to explain agentic AI to colleagues, identify realistic use cases, and prepare for hands on no code building in the next course.

Syllabus

Agentic AI Fundamentals

AI features are appearing in many workplace tools, but not all of them function the same way. Some systems simply answer questions, while others coordinate multiple steps to complete tasks across different tools. In this module, you will build a clear mental model of what AI agents actually are and how they differ from chatbots and traditional automation. You will examine core components such as goals, planning, tools, memory, and feedback loops, and learn the terminology used by product, engineering, and data teams. By the end of the module, you will be able to recognize agent-like behavior in everyday software and understand how these systems support real operational workflows.

Identifying High Value, Low Risk Use Cases

Many teams are experimenting with AI tools but struggle to decide where to start. In this module, you will learn how to identify practical opportunities for AI agents by examining the work you already do every day. You will map your tasks, analyze how workflows move through people and systems, and evaluate which processes are safe and valuable to automate. You will also learn how to assess risk, data sensitivity, and business impact so you avoid deploying AI in places where mistakes could cause real problems. By the end of this module, you will have a clear shortlist of workflows that are realistic candidates for your first AI agent projects.

Communicating and Collaborating on AI Agent Projects

You are often the bridge between business questions and technical delivery, and this module helps you make that bridge precise. You will learn to write short, operational AI agent briefs that name the business problem, identify target users and observable triggers, and define measurable success criteria. You will practice translating user stories into implementable agent behaviors—sequenced actions, required integrations, and simple escalation rules—and learn how to turn nontechnical concerns about reliability and explainability into monitoring plans using application programming interfaces, integrations, and activity logs. After completing this module, you will be able to produce a stakeholder-ready agent brief and recommend guardrails that enable safe, evaluable pilots.