Description

A one-day intensive workshop introducing LLMOps practices – or MLOps tailored to the specifics of large language models. You learn how to manage the lifecycle of GenAI applications in production: versioning prompts, automated testing, CI/CD pipeline, cost and quality monitoring, governance and security. Work on real tools of Azure or GCP platform – you choose the variant that suits your cloud. This is a workshop for teams that have stopped experimenting and need professional processes for implementing AI at the enterprise level.

For whom

AI/Cloud Architects, Technical Leaders, IT Managers, DevOps/MLOps Teams.

What you gain

You will understand the differences between MLOps and LLMOps and the specific challenges of prompts, context and evaluation. You will learn to build CI/CD pipelines for GenAI applications, automate testing prompts and monitor quality drifts. You will master the platform tools (Azure Prompt Flow or Vertex AI Pipelines) and evaluation metrics (Groundedness, Relevance, Fluency). You will receive a reference architecture and production readiness checklist for AI applications. You will leave with the knowledge of how to avoid chaotic implementations and costly mistakes.