1.1 Learning Roadmap¶
TThis workshop teaches you the capabilities of the Azure AI Foundry Portal with a set of interactive labs that take you from catalog (model selection) to cloud (application deployment). The labs are derived from the documentation but assembled into an end-to-end narrative for an AI Engineer journey.
1. Core Objectives¶
This workshop has two core objectives:
- Develop familiarity with the layout and capabilities of the Azure AI Foundry Portal (web UI)
- Learn how to build, evaluate, and deploy, a RAG-based generative AI app portal-first.
In this context, portal-first means that we prioritize using the Azure AI Foundry portal for the end-to-end developer workflow. By comprison, the Hybrid approach uses the Azure AI Foundry Portal (low-code) for setup and the Azure AI Foundry SDK (code-first) for ideation and evaluation.
2. Learning Journey¶
By completing the labs in this workshop, you will learn to do the following:
- Model Selection - use the Azure AI model catalog to discover and compare models.
- Project Setup - create an Azure AI hub & project with models and connected resources.
- Ideation - go from initial prompt to functional prototype using model (with & without data).
- Evaluation - learn about built-in and custom evaluators, run an evaluation flow & view results.
- Observability - learn about tracing and app insights, view run traces in the portal.
- Deployment - go from prototype to production by deploying an app and using the endpoint.
Along the way, we'll also understand how to orchestrate complex workflows in the portal using the currently-provided tooling (prompt flow) and a retrieval-augmented generation pattern (RAG) to improve responses by grounding them in your data.