School of Software Engineering Training 2025
20 - 22 May, 9:00 - 17:00 (CET)
*This course is now full, but please contact GLAD to be added to the waiting list.*
This training provides a pragmatic, no-nonsense approach to working with Large Language Models (LLMs). Instead of relying on hype, it emphasises foundational techniques—effective prompts, solid context management, and time-tested programming principles.
Participants will gain insights into building reliable and maintainable LLM-based applications using SpringAI or LangChain, without unnecessary complexity.
Additionally, the course covers evaluating LLM outputs, implementing observability practices, and managing deployment and scaling concerns. By the end of the training, participants will be equipped to deliver robust, efficient, and production-ready LLM solutions.
Training follows a hands-on approach where participants work on real-world LLM integration challenges. Workshop components include guided exercises building actual LLM-powered applications, from simple prompt engineering to complex multi-step workflows.
Participants will learn through practical implementation how to avoid unnecessary complexity while delivering robust solutions that meet business requirements. Each module builds upon previous knowledge, culminating in the development of production-ready LLM applications that demonstrate best practices in testing, observability, and scalability.
By focusing on pragmatic techniques rather than theoretical abstractions, participants will leave with immediately applicable skills for implementing LLM solutions in their organisations.
Requirements:
- Minimum of two years experience in creating IT systems (technical or non-technical).
- Python or Java environment.
- Own computer with setup IDE and internet access.
Eligible participants can claim their time for this workshop through the GN5 project. See guidelines and eligibility criteria here >