This hands on course teaches you to build practical AI agents using free or freemium no code tools, even if you have never written a line of code. You will start by translating a simple real world workflow into a series of triggers, conditions, and actions that an AI agent can execute. Using platforms such as Vellum, Zapier, Make, Power Automate, or Dify, you will configure agents to manage tasks, schedule meetings, and send follow up messages. The course emphasizes safe experimentation: you will work in sandbox environments, use dummy data, and keep humans in the loop. You will practice debugging misbehaving agents, improving prompts, and refining workflows based on observed behavior. By the end, you will have at least one working AI agent that automates a personal or team workflow involving calendars, reminders, or lightweight coordination tasks.

This course teaches you how to assess and improve the quality, safety, and business impact of the AI agents you create. You will learn straightforward techniques for evaluating outputs, measuring reliability, and reducing hallucinations and errors. The course covers beginner friendly security, privacy, and governance practices so your agents align with organizational policies and regulations. You will design simple experiments to compare processes with and without agents, quantify time savings, and communicate results to managers. Finally, you will explore how to maintain, document, and responsibly scale your agents without creating unmanageable “agent sprawl.” By the end, you will be able to define clear output requirements, evaluate your agents systematically, and make evidence based decisions about when and how to deploy them.