content & syllabus
Participants will explore four major prompt-engineering pattern categories: guiding, shaping, refining, and formalizing – and apply them to real engineering and quality tasks. They will learn how to define productivity goals, measure value, and identify high-impact generative-AI use cases within their teams. The course then dives deep into AI-driven testing techniques such as vision-based automation, predictive modeling, clustering, and reinforcement learning, and shows how large language, vision and action models are enhancing existing AI capabilities. Lastly, the day concludes with an evolutionary approach for evaluating chatbots, LLM-based assistants, and autonomous AI agents.
Through guided labs, collaborative exercises, and practical demonstrations, attendees will leave equipped with actionable skills to harness generative AI for speed, quality, and innovation across their software development lifecycle.
target group
For experienced software testers who already have a background in using generative artificial intelligence (GenAI) to support their work and now want to take it to the next level.
prerequisites
The course requires experience in software testing and in the application of generative artificial intelligence.
exam & certification
There is no exam for this course. Participants will receive a certificate of attendance.
benefits and discounts
We know that you can learn best when you feel comfortable and when we meet as many of your expectations as possible. That's why you not only get a first-class training, but also a wide range of training and certification services. Read more about the benefits of training with trendig and what is included in our courses here:
