When you work with large machine learning models (like LLMs), the development process can get messy, fast. To address this, the workshop equipped participants with MLOps practices and tools to maintain reproducibility, automation, and testability.

The workshop began with the fundamentals of building a chatbot using LLMs. Then, it transitioned to demonstrating how to take a prototype and iteratively adapt it to a real-world scenario using software like data version control (DVC). By the workshop's conclusion, attendees had built a working pipeline that connected LLMs, a custom dataset, and crucial performance metrics.

You can view and download the workshop presentation slides below.

Anyone who wants to learn how to practically build an AI application like a chatbot, and how to incorporate MLOps tools into its development. No previous AI or ML experience is required.