Generative AI for QA Engineers Agents, RAG, LLM testing

Testing Agents, RAG, LLMs & GenAI Tools for Modern QA Workflows

What you'll learn
- Master AI Agent Application Testing: Learners will be able to design and execute comprehensive testing strategies for LLMs, RAG systems, and AI Agents
- Implement Autonomous AI Testing with Agents: Learners will apply agentic AI techniques to build autonomous testing workflows using browser agents and tools
- Enhance Traditional QA with Generative AI: Learners will leverage generative AI tools like ChatGPT and GitHub Copilot to generate test cases and automation
- Utilize Modern AI Testing Tools: Learners will gain hands-on experience with cutting-edge tools like TestRigor and AutoPlaywright

Requirements
- This course is designed to be accessible yet impactful. While no deep AI expertise is required, the following foundational skills and tools will help learners get the most out of the experience:
- Basic Python Knowledge: Learners should be comfortable writing simple Python scripts, using functions, and understanding basic data structures (lists, dictionaries, etc.).
- Software Engineering or QA Background: A general understanding of software development or quality assurance processes (like test cases, bug reports, automation basics) is expected.
- Familiarity with Common Tools: Experience with tools like Git, VS Code, and basic command-line usage will be helpful for hands-on labs.
- System Requirements: A laptop or desktop with internet access, the ability to install Python packages, and access to platforms like GitHub and Google Colab or Jupyter Notebook.

Description
AsAIrapidly transforms the software industry, the role ofQAis evolving just as fast. This course is designed to helpQA professionalsstay ahead by equipping them with the practical skills needed to test modernAI applicationsand integrateGenerative AI into traditional QA workflows.

Whether you're testingLLMs, RAG systems, or building autonomous agent-based testingpipelines, 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 Engineersexpanding into AI-powered testing

Software Testerseager to understand and validate LLMs, RAG, and Agentic systems

Test Leads and QA Managersaiming to modernize team processes using Generative AI

Automation Engineersexploring agent-based, intelligent testing frameworks

By the end of this course, you'll be equipped toconfidently test AI applications, implement autonomous testing agents, and integrate Generative AIinto your existing QA toolkit—future-proofing your role in the age of intelligent software.

Who this course is for:
- This course is specifically designed for professionals in the software testing and quality assurance domain who are looking to upskill in the fast-evolving field of AI testing. It will be especially valuable for:
- QA Engineers looking to expand their skillset into AI-powered testing tools and techniques.
- Software Testers aiming to understand how to test AI applications like LLMs, RAG systems, and Agents
- Team Leads and QA Managers who want to drive innovation in their teams by integrating AI tools into traditional testing workflows.
- Automation Engineers seeking to explore autonomous testing using Agentic AI and modern test frameworks.
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