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Integration of AI assistants such as ChatGPT, Claude, and Google Bard for seamless testing automation
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Practical assignments and real-world examples designed for hands-on experience in applying AI to functional and API testing
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Building automated testing frameworks from scratch using AI and implementing data-driven testing techniques
This course guides QA professionals through the integration of Generative AI (GenAI) into their software testing strategies. Starting with foundational knowledge, it demonstrates how to set up and use AI assistants like ChatGPT, Claude, and Google Bard for testing tasks. You’ll automate functional, API, and mobile app testing, as well as generate test data and write better bug reports. Each lesson builds upon the previous one to streamline workflows and improve accuracy through AI.
The course also covers advanced topics such as building AI-driven web automation frameworks and implementing self-healing tests using TestRigor. With a focus on minimizing maintenance, improving stability, and reducing manual effort, you’ll master techniques for creating low-maintenance tests. Practical examples allow you to apply what you’ve learned to real-world scenarios, integrating AI into your testing processes.
By the end of the course, you’ll be equipped to automate repetitive tasks, enhance code quality, and increase productivity. Whether you're new to QA automation or looking to expand your skill set, this course provides the tools and knowledge to make AI a core part of your testing strategy.
This course offers a hands-on, project-based learning approach, combining theory with practical examples. Each module builds upon the last, ensuring you progress from basic concepts to advanced techniques. By the end of the course, you will confidently use GenAI in your daily QA tasks.
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Set up and configure AI tools like ChatGPT, Claude, and Google Bard for effective QA automation
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Master prompt engineering to optimize AI responses for QA tasks
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Create automated functional test cases for web, mobile, and API applications
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Develop efficient, data-driven tests and reduce test maintenance with AI-powered tools
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Implement self-healing tests using TestRigor to ensure high test stability
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Leverage AI to generate test data and write better bug reports, improving overall testing efficiency
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