Agentic AI for QA Automation with Python

About this course

This course is designed for QA Engineers, Automation Engineers, SDETs, and Developers who want to build AI-assisted, controlled, and production-ready agent systems for software testing and automation.

Rather than focusing on isolated AI prompts, this course teaches Agentic AI principles—how to design AI systems composed of multiple agents that can reason, collaborate, and take actions within clearly defined boundaries.

Step into the future of Artificial Intelligence with Agentic AI Fundamentals. This course teaches you how to design, build, and deploy autonomous AI agents using Python, AutoGen, multimodal models, and modern agent orchestration techniques. From async programming to browser automation with Playwright MCP, you’ll gain the hands-on skills to create scalable AI systems with human-in-the-loop controls, advanced state management, and multi-agent collaboration.

Using Python and the AutoGen framework, you will learn how to build text-based and multimodal AI agents, orchestrate multi-agent workflows, manage agent state, and implement termination logic to keep AI behavior predictable and safe. You will also learn how to apply human-in-the-loop controls, enabling AI systems to request validation or approvals when needed.

The course places strong emphasis on enterprise-safe AI design, showing how agents can interact with real systems using MCP tools and browser automation with Playwright MCP, while maintaining governance and control.

Every module is hands-on and implementation-focused, designed to help you build scalable AI-assisted QA workflows, not experimental prototypes.

What you will be able to do after this course

Design AI-assisted QA agents using Agentic AI principles

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