This multi-part workshop series provides enterprise Python developers and technical stakeholders with best practices for Understanding Natural Language User Requests end-to-end. It begins with a Foundational Introduction class (for both technical and non-technical audiences) to establish core concepts and context for natural language understanding. Subsequent workshops dive into technical implementation details, each targeting a specific stage of the NLU pipeline. The series is carefully structured to avoid repetition by clearly delineating which module covers each concept in depth. Attendees will gain a comprehensive, layered understanding – from basic text parsing to intent classification, entity extraction, semantic interpretation, ambiguity resolution, and continual improvement of NLU systems. 

Note: The introduction session covers high-level concepts (e.g. what intents and entities are, an overview of machine learning vs. rule-based approaches, etc.) to ensure all participants share a common vocabulary. Technical details and hands-on practice are reserved for the dedicated deep dives in Workshops 1–6.