Learn Generative AI in Software Testing
Learn Generative AI in Software Testing and Prompt engineering skills to generate Test Artifacts, Automation codes and demo of AI powered Testing tools
What you will learn
- Learn Prompting skills to generate Automation code in any language/tools (Selenium,Cypress,Playwright) using AI
- Understand how to optimize the code into framework standards with simple prompting to AI
- Learn generating Test Artifacts in fly such as TestPlan, Testcases, TestData, Bug templates for given Business requirements
- Get overview of AI Powered Testing tools in current market and their capabilities for revolutinizing Test Automtion
- Learn generating API Automation tests to framework level & SQL Queries with simple prompting to AI
Why take this course?
🚀 Course Title: Learn Generative AI in Software Testing 🎓
Course Headline:
Unlock the Power of AI for Efficient Software Testing!
Course Description:
Embark on a transformative journey with our comprehensive online course, designed to equip you with the cutting-edge skills of prompt engineering to harness the capabilities of Generative AI in software testing. This AI Testing course is your gateway to generating test artifacts, automation codes, and experiencing a live demo of an AI-powered testing tool. Learn how to interact with AI intelligently, asking the right questions to receive accurate and timely responses that cater to your everyday testing needs.
🔍 What You Will Explore:
- Phase 1: Generative AI in Test Planning & Execution
- Creating AI-driven test plans and requirements
- Generating unit, integration, and functional test cases
- Producing relevant test data for diverse testing scenarios
- Developing automation scripts for test cases
- Crafting custom utility code methods to automate repetitive tasks
- Configuring framework-related files using AI insights
- Writing Cucumber feature files and step definitions with real, working code
- Producing UI tests using popular libraries like Selenium, Cypress, and Playwright
- Phase 2: AI-Powered Testing Tools & Codeless Automation
- An introduction to the landscape of AI-powered testing tools
- Achieving codeless automation with AI QA tools
- Generating test automation code from business analyst requirements
- Exploring self-healing capabilities to maintain test stability
- Understanding intelligent reporting and defect management systems
- Conducting a hands-on demo of writing complex tests in plain English
- Phase 3: Advanced AI Applications in Testing
- Parsing JSON responses with simple AI prompts
- Generating JSON paths using natural language
- Creating POJO classes from complex JSON files using AI prompts
- Developing Rest Assured automation tests using contract documentation
- Generating custom utility code methods to validate API responses on-the-fly
- Producing AI-driven tests for web applications and APIs using libraries like Rest Assured, Cypress, and Playwright
- Formulating SQL queries from complex database tables with the help of AI
Why This Course?
- Practical Application: Learn through real-world scenarios and live demonstrations.
- Hands-On Experience: Engage in hands-on exercises that solidify your understanding.
- Cutting-Edge Knowledge: Stay ahead of the curve with the latest advancements in AI for testing.
- Expert Guidance: Be mentored by Rahul Shetty, an experienced professional in software testing and Generative AI.
Join us to redefine the boundaries of software testing and leverage the full potential of AI to streamline your processes, enhance productivity, and ensure top-quality software delivery. 🌟
Enroll now and transform your approach to software testing with Generative AI! 🚀✨
Our review
Course Review for Generative AI in Software Testing
Overall Rating: 4.53
Recent Reviews Summary:
Pros:
- Comprehensive Coverage: The course covers all topics with a nice presentation, making it easy to understand and apply in day-to-day work. It’s particularly helpful for career growth in the QA field.
- Exceptional Teaching: Rahul Shetty is praised for his amazing teaching skills, being highly technical yet detailed in his training. The mentor is considered the best QA tutor among many learners.
- Engaging Structure: The course structure is described as awesome, boosting confidence for those working as QAs after completing the course.
- Knowledge Acquisition: Learners report getting good knowledge in using AI tools for software testing, including test cases, test plans, and automation scripts. It also includes techniques for prompt engineering, which is highly beneficial.
- Valuable Resource: The course serves as a fantastic introduction to AI in software testing, providing a great overview and diving deeper into specific techniques. It’s considered valuable by those eager to explore the future of software testing.
- Well-Structured Content: The content is well-structured, easy to follow, and articulated clearly from manual to automated code less AI powered tools. This makes it a must-watch course for software testers.
- Practical Application: Real-world use cases are demonstrated, allowing learners to apply generative AI to various testing activities such as test case generation, defect prediction, and NLP.
- Prompt Engineering Focus: The course includes a valuable lesson on prompt engineering, equipping testers with the skills to effectively interact with AI models.
Cons:
- More Examples Needed: Some learners suggest that Rahul Shetty could have shown more SQL examples or gone deeper into other aspects for a more comprehensive learning experience.
- Documentation: There is a call for more documentation within the course, as some feel there is currently less documentation available.
- Advanced Topics: Learners express a desire for a deeper dive into more advanced topics and domains, including fine-tuning AI models and addressing ethical considerations in AI testing.
- In-Depth Content Desired: The course is seen as only providing a basic introduction to Gen AI tools and prompting, with some learners feeling it doesn’t fully justify the hype created around it.
- Advanced Explanation Needed: Some feedback indicates that while the course gives an amazing introduction to leveraging AI in QA tasks, more content on creating custom functions, framework designing using AI, and insights into how QA will evolve in the next few years would be beneficial.
Conclusion:
This course is a solid starting point for those interested in exploring the potential of generative AI in software testing. The instructor’s expertise and clear explanations make the content engaging and easy to follow, with a strong emphasis on prompt engineering. However, learners anticipate that more advanced content and topics would enhance its value even further. It’s recommended for QA engineers looking to leverage AI in their day-to-day tasks to reduce manual efforts and understand the insights into the future of QA.
Created by Rahul Shetty
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