GenAI & AI Agents for QA Automation | Copilot & Claude code
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Unclaimed ProfileThe GenAI & AI Agents for QA Automation masterclass from Rahul Shetty Academy is a game-changer for software testers, quality assurance engineers, and automation developers aiming to stay ahead of the technology curve. As artificial intelligence redefines the software development lifecycle, this course provides hands-on, practical strategies to integrate cutting-edge tools like GitHub Copilot, Claude Code, and n8n into your daily testing workflows. Students will explore the shift from manual and traditional scripting to advanced agentic solutions, learning how Model Context Protocol (MCP) servers can transform standard LLMs into specialized automation agents. Beyond simple prompt engineering, the curriculum guides you through building codeless browser automation, optimizing Selenium frameworks at the terminal level, and generating robust test artifacts—including test plans, edge-case test data, and bug reports—instantly from business requirements. Crucially, the course also addresses enterprise privacy concerns by demonstrating how to deploy and customize offline LLMs. Whether you are looking to dramatically accelerate your manual testing pipelines or modernize complex CI/CD automation frameworks, this course equips you with the future-proof skills needed to lead AI-driven QA initiatives in any organization.
About the creator
Rahul Shetty Academy
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Rahul Shetty Academy is a premier online training hub dedicated to software testing, test automation, and modern AI-driven development. Founded by Rahul Shetty, a pioneer in QA education, the academy focuses on bridging the gap between theoretical software engineering and hands-on, industry-ready implementation. Our teaching methodology is centered around "learning by doing." Rather than focusing purely on syntax, we guide students through building robust, real-world framework architectures from scratch. With the rapid evolution of technology, we have expanded our curriculum from foundational Selenium and Playwright automation frameworks in Python, JavaScript, and TypeScript to cutting-edge AI integrations. This includes training on…Show more
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Program Overview
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Learning format
Subcategory
Price
Price may change · updated within 1–2 weeks
Course language
What You'll Learn
- Learn how to use Gen AI LLM's effectively to maximize your QA Productivity with smart prompt engineering skills
- Understand how to Generate & optimize the Test code into framework standards with Gen AI Plugins such as Github copilot etc
- Understand how MCP Servers work & how they can boost LLM to be specialized Automation AI Agents
- Get overview of AI Powered Testing tools in current market and their capabilities for revolutionizing Test Automtion
- Learn how AI Agents work and how they can be used to perform Codeless browser Automation with help of LLM's
- Learn the power of AI at terminal level using Claude code with practical Selenium Framework example
- Learn n8n basics & build Automation workflows powered by AI Agents
- Understand how to work with offline LLM's with full privacy and customize the LLM as per your project requirements
- Learn generating Test Artifacts in fly such as TestPlan, Testcases, TestData, Bug templates for given Business requirements
Best For
- QA automation engineers looking to integrate LLMs into existing Selenium or Playwright frameworks.
- Software testers aiming to automate the generation of test plans, bug reports, and complex test data.
- DevOps and QA professionals interested in building agentic workflows with n8n and terminal-based tools.
- Developers wanting to leverage GitHub Copilot and Claude Code for accelerating script writing and framework maintenance.
Not For
- Absolute beginners with no prior knowledge of software testing concepts or automation fundamentals.
- Data scientists or AI researchers focusing on model training or machine learning architecture rather than practical QA applications.
- Professionals seeking a theoretical course on the history of AI instead of hands-on, implementation-heavy tutorials.
- Those looking for non-technical leadership advice on AI implementation without hands-on coding requirements.
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