Do not treat this objective as a recognition exercise. Practise explaining and applying 'Build generative applications by using Foundry: Deploy and consume LLMs, small models, code models, and multimodal models' in a new scenario, then check your reasoning against the official source. Source context: Read in English Select, deploy, and evaluate Microsoft Foundry models Module 8 Units Feedback Intermediate Data Scientist AI Engineer Microsoft Foundry Explore how to select appropriate models from the model catalog using benchmarks, deploy them to endpoints, and evaluate their performance using manual and automated approaches in Microsoft Foundry portal. Learning objectives By the end of this module, you'll be able to: Explore and filter models in the model catalog Compare models using benchmark metrics for quality, safety, cost, and performance Deploy a model to an endpoint and test it in the playground Evaluate model performance using manual and automated approaches Understand different evaluation metrics and when to use them Add Prerequisites Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Introduction min Explore the model catalog min Select models using benchmarks min Deploy models to endpoints min Evaluate model performance min Exercise - Select, deploy, and evaluate models min Knowledge check min Summary min Take the module assessment Module Assessment Results Assess your understanding of this module.
Objective
Build generative applications by using Foundry: Deploy and consume LLMs, small models, code models, and multimodal models