Module 1 AI Basics.

This module provides a structured introduction to fundamental AI concepts and terminology. It explains how modern AI systems operate and examines key concepts such as chatbots, fine-tuning, and Retrieval-Augmented Generation (RAG), with a focus on their relevance to Requirements Engineering.

Module 2 Large Language Models (LLMs).

This module explains the underlying principles of Large Language Models (LLMs). It focuses on their probabilistic and pattern-based behavior and discusses the implications of these characteristics for the effective and responsible use of AI in Requirements Engineering.

Module 3 – Prompt Engineering.

This module introduces core principles and techniques of prompt engineering. Learners develop the skills needed to structure prompts effectively in order to guide AI outputs and improve their usefulness within Requirements Engineering activities.

Module 4 – Risks and Responsibilities of AI in Requirements Engineering.

This module addresses the key risks, limitations, and responsibilities associated with the use of AI in Requirements Engineering. It enables learners to identify potential issues and apply appropriate controls to ensure quality, reliability, and responsible use.

Module 5 – Use Cases for AI in Requirements Engineering.

This module explores practical use cases for applying AI across Requirements Engineering activities, including elicitation, documentation, validation, and requirements management. Emphasis is placed on maintaining human oversight and ensuring that the Requirements Engineer remains accountable for quality and decision-making.