About This Workshop
Large Language Models are powerful tools, but using them effectively requires more than prompt crafting. This workshop builds practical intuition for how modern AI systems work by examining the mechanics behind tokenization, embeddings, vector search, transformer architectures, and retrieval‑augmented generation. Through hands‑on exercises, participants learn how to evaluate use‑cases, reduce risk, and design applications that integrate AI responsibly and reliably. No prior AI experience is required; familiarity with software development concepts is helpful.
This full‑day workshop provides a practical, engineering‑focused understanding of how modern language models operate and how to apply them effectively in real systems. Participants explore the full lifecycle of text processing, from tokenization to embeddings to transformer inference, and learn how these components shape model behavior.
The workshop emphasizes applied techniques: building and comparing embeddings, performing semantic search, integrating vector databases, designing retrieval‑augmented generation pipelines, and evaluating model output for reliability and safety. Attendees work through hands‑on exercises using local or cloud‑based tools to reinforce concepts and build confidence in applying AI to real‑world problems.
By the end of the day, participants will understand when and why to use LLMs, how to structure data for them, how to reduce hallucinations, and how to design systems that are transparent, ethical, and maintainable.