AiU-Certified GenAI-Assisted Test Engineer

Overview

As pioneers in the integration of Artificial Intelligence (AI) within testing frameworks, we at Artificial Intelligence United (AiU) are thrilled to unveil our latest offering: the Certified GenAI-Assisted Testing Engineer (GenAiA-TE) course! In just three days, you'll embark on a journey through seven comprehensive chapters, each meticulously designed to equip you with cutting-edge knowledge and practical skills:

  • GenAI-Assisted Testing: Discover the evolution of testing from manual to AI-assisted methodologies. Learn the inner workings of Language Model-based AI, its benefits in efficiency and human-guided testing, and how to overcome challenges in its implementation.
  • Prompt Engineering: Master the art of crafting effective prompts, essential for guiding AI in generating high-quality test cases. Adapt to changes seamlessly and maintain quality standards with insights from seasoned professionals.
  • Requirements Review: Capturing requirements is a critical step in a development life cycle, as this is where one or more individuals try to express, usually a vague notion of what is to be built in a recorded format. There can be many issues in this translation of what is supposed to be built (which could have its own issues in understanding) versus what is captured. Requirement review is a stage for one of the earliest forms of testing where testers can contribute to improving the requirements. Given the inherent complexity of requirement reviews, AI can greatly assist a tester.
  • Test Generation and Optimization: Explore diverse aspects of test design, leveraging AI efficiently, experimenting with formats, and incorporating systematic techniques. Unleash your creativity with open-ended test idea exploration while considering technology and non-functional testing factors.
  • Test Data: Harness the power of AI for data representation and generation, mastering techniques like regular expressions to manipulate data effectively in various formats.
  • Bug Advocacy and Reporting: Large Language Models built on Natural Language Processing are especially powerful at generating and evaluating textual content in various formats. A tester can use this power to advocate bugs better by writing reports that sell.
  • Further Steps: Beyond the scope of this course, there are still many current and future possibilities for AI assistance in testing. This concluding section gives a glimpse of these opportunities. It also shows how AI is not a full replacement for human intellect and how, in combination, these two forms of intelligence can do magic.
GenAI
Business Outcomes
  • Stay Ahead: Position yourself at the forefront of the testing field by integrating AI into your skillset.
  • Practical Skills: Gain hands-on experience with real-world projects and scenarios that prepare you for immediate industry impact. 90% of the training is hands-on.
  • Expert Instructors: Learn from leaders in the field, bringing you the latest insights and techniques from the world of AI testing.
Audience

The AiU Certified GenAI-Assisted Test Engineer (GenAiA-TE) certification is designed for software testing professionals who would like to use the possibilities of GenAI in their daily work to maximize their software quality assurance contributions. This certification course will change how you work and bring you to state-of-the-art AI-assisted testing.

Eligibility

Prerequisites

  • Hands-On testing experience
  • ISTQB CTFL or Equivalent Subject Knowledge specifically on test design techniques - ECP, BVA, Decision Tables and State Transition Testing

Technical/Equipment Requisites

  • Laptop
  • Good Internet Connectivity
  • ChatGPT Account
  • (Preferrable) RDP Software to connect to a remote lab machine
  • NO Programming experience is required.
Certification Providers

Artificial Intelligence United

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Certified Tester – Testing with Generative AI (CT-GenAI)

The updated of the ISTQB® Certified Tester – Testing with Generative AI (CT-GenAI) syllabus builds upon the strong foundation established in version 1.0, further enhancing its practical relevance to today’s rapidly evolving AI-driven testing landscape. Expanding on the original concepts, the updated syllabus provides testing and quality-engineering professionals with a more comprehensive and market-aligned learning path for effectively applying Large Language Models (LLMs) and Generative AI techniques across the entire testing lifecycle — from requirements analysis and test design to automation, reporting, and continuous improvement. The enhanced syllabus places greater emphasis on real-world industry applications, advanced prompt-engineering practices, and emerging AI-assisted testing use cases that reflect current market demands. In addition to strengthening core GenAI fundamentals, version 1.1 equips testers with practical strategies for responsible AI adoption, including the management of risks such as hallucinations, bias, security, privacy, and environmental impact.

Specialist
GenAI Testing