Learn AI in Software Testing - Venkatesh (Rahul Shetty)
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Learn AI in Software Testing with Venkatesh (Rahul Shetty) Academy. This course helps you understand AI automated testing in a simple way. Unlock the next level of software testing. This comprehensive course integrates cutting-edge AI techniques with industry-standard testing tools to streamline automation, boost accuracy, and reduce manual effort. Designed for QA professionals, developers, and test engineers, it offers practical insights and hands-on experience to help you stay competitive in the rapidly evolving tech landscape. Future-proof your QA career by mastering AI-driven testing strategies and gaining a strong edge in the industry.
Learn AI in Software Testing - Venkatesh (Rahul Shetty)
- 1. LEARN AI IN SOFTWARE TESTING - VENKATESH (RAHUL SHETTY) T R A N S F O R M I N G Q U A L I T Y A S S U R A N C E W I T H I N T E L L I G E N T A U T O M A T I O N
- 2. INTRODUCTION TO SOFTWARE TESTING • What is Software Testing? • Importance in the SDLC • Traditional vs. Modern Testing • Challenges in Manual and Automated Testing
- 3. WHY AI IN SOFTWARE TESTING? • Increasing test complexity • Demand for faster releases (Agile/DevOps) • AI reduces repetitive tasks and human errors • Enhances accuracy, speed, and test coverage
- 4. KEY APPLICATI ONS OF AI IN TESTING • Test case generation using ML models • Predictive analytics for risk-based testing • Visual testing using image recognition • Intelligent test data generation • Smart bug detection and classification
- 5. AI-POWERED TEST AUTOMATION TOOLS • Tools using AI: Testim, Applitools, Mabl • AI in Selenium-based frameworks (e.g., self-healing locators) • Example: How AI fixes flaky tests automatically
- 6. HOW AI WORKS IN TEST AUTOMATION • Natural Language Processing (NLP) for test script generation • Machine Learning models trained on past test results • Pattern recognition in UI changes • Predictive failure analysis
- 7. BENEFITS OF USING AI IN TESTING • Faster feedback cycles • Reduced maintenance cost • Higher test coverage • Real-time defect prediction • Smarter test prioritization
- 8. CHALLENGES & LIMITATIONS • Requires high-quality data for training • High initial investment • Not all tasks are suitable for AI • Human oversight is still necessary
- 9. FUTURE OF AI IN TESTING • Autonomous Testing • Integration with CI/CD pipelines • Shift from scripted to adaptive testing • Growing role in performance & security testing
- 10. CONCLUSIO N • AI is revolutionizing software testing, making it smarter and faster • It complements, not replaces, testers • Upskill with platforms like Rahul Shetty Academy to stay ahead • Explore AI-augmented testing tools and stay future-ready!
- 11. CONTACT US +1 3237 446 780 www.rahulshettyacademy.com [email protected]
- 12. THANK YOU!