Course Overview:

This course provides an in-depth introduction to the role of Artificial Intelligence (AI) in software testing. It covers the fundamental concepts of both software testing and AI, focusing on how AI-driven tools and techniques can improve the efficiency, accuracy, and effectiveness of the testing process. The course is designed to introduce testers, developers, and IT professionals to the rapidly evolving field of AI-powered testing, exploring its applications, benefits, challenges, and future trends. Participants will learn how to leverage AI to optimize test generation, execution, and maintenance, thereby enhancing their software development lifecycle (SDLC).

Learning Objectives: By the end of this course, participants will be able to:

  1. Understand the basics of software testing and the types of testing involved in the SDLC.

  2. Gain basic knowledge of AI and machine learning concepts and how they can be applied to software testing.

  3. Explore AI-driven testing tools and techniques for test case generation, execution, and maintenance.

  4. Understand the advantages and limitations of incorporating AI in testing.

  5. Learn how to apply AI to optimize test coverage, defect prediction, and self-healing automation scripts.

  6. Examine real-world examples and case studies that illustrate the impact of AI on modern software testing practices.

  7. Understand the future trends of AI in software testing and its role in enabling continuous testing in DevOps pipelines.

Who Should Attend: This course is ideal for: Manual and Automated Testers looking to expand their skills in AI-driven testing. Developers interested in understanding how AI can enhance test automation. Quality Assurance (QA) professionals aiming to optimize their testing strategies with cutting-edge technologies. DevOps Engineers focused on integrating AI into continuous testing and delivery pipelines. IT Managers and Leaders seeking to understand how AI can improve software quality and reduce time-to-market.