Overview

As AI rapidly transforms the software industry, the role of QA is evolving just as fast. This course is designed to help QA professionals stay ahead by equipping them with the practical skills needed to test modern AI applications and integrate Generative AI into traditional QA workflows.Whether you're testing LLMs, RAG systems, or building autonomous agent-based testing pipelines, this course will provide you with step-by-step guidance, hands-on experience, and a strong foundation in AI-powered quality assurance. What You'll Learn:Module 1: Master AI Agent Application TestingDesign and implement comprehensive testing strategies to test Agents, Retrieval-Augmented Generation (RAG) systems, and LLM applications using cutting-edge tools and frameworks.Module 2: Implement Autonomous AI Testing with AgentsLearn to build autonomous, low-intervention testing workflows using browser agents, mcp and tools that simulate real user behavior.Module 3: Enhance Traditional QA with Generative AIUse tools like ChatGPT, GitHub Copilot, and DeepSeek to generate test cases, automation scripts, bug reports, and enhance everyday QA activities.Module 4: Utilize Modern AI Testing ToolsGet hands-on with tools like TestRigor, Playwright MCP Server, and Applitools to enable intelligent automation, smart UI testing, and rapid test generation. Are There Any Prerequisites?No deep AI expertise is needed, but learners should have the following to get the most out of this course:Basic Python Knowledge: Ability to write simple scripts and work with lists, dictionaries, and functions.QA or Software Engineering Background: Familiarity with test cases, bug reporting, or automation principles.Comfort with Tools: Experience with Git, VS Code, and command-line operations is helpful.System Setup: A computer with internet access, Python installation capabilities, and access to GitHub, Google Colab, or Jupyter Notebook.Who This Course Is For:This course is ideal for professionals in the QA and software testing space who want to embrace the future of AI in testing, including:QA Engineers expanding into AI-powered testingSoftware Testers eager to understand and validate LLMs, RAG, and Agentic systemsTest Leads and QA Managers aiming to modernize team processes using Generative AIAutomation Engineers exploring agent-based, intelligent testing frameworksBy the end of this course, you'll be equipped to confidently test AI applications, implement autonomous testing agents, and integrate Generative AI into your existing QA toolkit-future-proofing your role in the age of intelligent software.

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