Explores Microsoft’s Applied Skills credential program and the learning path for implementing a data science and ML solution with Microsoft Fabric, including setting up a Microsoft Learn profile, locating credential offerings, and following the guided scenario using Fabric’s Lakehouse, Notebooks, and MLflow integration. Linda Larkan will provide demonstrations highlighting the workflow from data ingestion to model training and prediction.

Learn how to set up MLflow for LLM tracing and monitoring in this practical session. We’ll walk through the basics of capturing execution traces from language model applications and explore how MLflow can help you track and debug your LLM workflows. Using straightforward LangChain examples, you’ll see how to implement basic tracing functionality to gain better visibility into your model’s behavior and performance. An introduction for data scientists and ML engineers who want to add observability to their language model projects. We will also go into managing the lifecycle of experiments, runs and traces.

O’Reilly usage analysis shows continued growth in AI/ML and early signs that organizations are experimenting with advanced tools and methods.