AI for Software Testing

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Course Overview

The future of software testing lies at the intersection of human ingenuity and technological advancement. Our AI for Software Testing course is an immersive and interactive journey designed to prepare experienced software testers for a future driven by AI in software testing and test automation.

Through hands-on exercises with leading AI tools and agents, you’ll gain real-world experience generating critical testing artefacts—from system-level test plans to individual test cases. While AI can automate repetitive tasks like test case generation, its capabilities extend much further across the testing process.

You will explore how to apply artificial intelligence to evaluate existing tests, structure systems for more effective software quality practices, interpret test results, and maintain traceability from requirements to test cases. By combining human expertise with AI in software testing, you’ll learn how to leverage machine learning and intelligent agents to optimize test automation efforts.

As a modern software tester, understanding the role of AI in software testing will be critical. This testing course empowers you to lead testing initiatives that incorporate automation thoughtfully—enhancing efficiency without sacrificing critical human oversight. Whether you're transitioning from manual testing or enhancing existing automated frameworks, testing with AI will give you the edge.

Who Should Attend

• Testers, Test Analysts and Developers wanting to utilize AI to automate and assess testing tasks and artefacts.
• Project Managers, Business Analysts and leaders wanting to accelerate the testing process whilst balancing responsible and ethical oversight.
• Anyone looking to be skilled in AI augmentation and innovation.

Course Objectives

• Developing test cases, executable automated test scripts and test suites with the assistance of AI.
• Evaluating strengths and weaknesses of AI created test artefacts.
• Testing against specifications more thoroughly with AI augmentation.
• Employing AI to design combinatorial and exploratory test sets.
• Analyzing test results and defect reports using AI.
• Developing test plans for non-functional requirements with AI.
• Incorporating agile user stories into testing using AI.
• Utilizing AI to amplify manual testing efforts.

Course Outline