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Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.

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What You'll Learn

  • Identify common AI capabilities that you can implement in applications
  • Describe Azure AI Services and considerations for using them
  • Describe Azure AI Foundry and considerations for using it
  • Identify appropriate developer tools and SDKs for an AI project
  • Describe considerations for responsible AI
  • Select a language model from the model catalog.
  • Deploy a model to an endpoint.
  • Test a model and improve the performance of the model.
  • Describe capabilities of the Azure AI Foundry SDK.
  • Use the Azure AI Foundry SDK to work with connections in projects.
  • Use the Azure AI Foundry SDK to develop an AI chat app.
  • Understand the development lifecycle when creating language model applications.
  • Understand what a flow is in prompt flow.
  • Explore the core components when working with prompt flow.
  • Identify the need to ground your language model with Retrieval Augmented Generation (RAG)
  • Index your data with Azure AI Search to make it searchable for language models
  • Build an agent using RAG on your own data in the Azure AI Foundry portal
  • Understand when to fine-tune a model.
  • Prepare your data to fine-tune a chat completion model.
  • Fine-tune a base model in the Azure AI Foundry portal.
  • Describe an overall process for responsible generative AI solution development
  • Identify and prioritize potential harms relevant to a generative AI solution
  • Measure the presence of harms in a generative AI solution
  • Mitigate harms in a generative AI solution
  • Prepare to deploy and operate a generative AI solution responsibly
  • Understand model benchmarks.
  • Perform manual evaluations.
  • Assess your generative AI apps with AI-assisted metrics.
  • Configure evaluation flows in the Azure AI Foundry portal.

Who Should Attend

N/A

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Prerequisites

Before starting this module, you should be familiar with fundamental AI concepts and services in Azure. Consider completing the Get started with artificial intelligence learning path first.

Learning Journey

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1. Plan and prepare to develop AI solutions on Azure

Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Proper planning and preparation involves identifying the services you'll use and creating an optimal working environment for your development team.

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2. Choose and deploy models from the model catalog in Azure AI Foundry portal

Choose the various language models that are available through the Azure AI Foundry's model catalog. Understand how to select, deploy, and test a model, and to improve its performance.

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3. Develop an AI app with the Azure AI Foundry SDK

Use the Azure AI Foundry SDK to develop AI applications with Azure AI Foundry projects.

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4. Get started with prompt flow to develop language model apps in the Azure AI Foundry

Learn about how to use prompt flow to develop applications that leverage language models in the Azure AI Foundry.

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5. Develop a RAG-based solution with your own data using Azure AI Foundry

Retrieval Augmented Generation (RAG) is a common pattern used in generative AI solutions to ground prompts with your data. Azure AI Foundry provides support for adding data, creating indexes, and integrating them with generative AI models to help you build RAG-based solutions.

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6. Fine-tune a language model with Azure AI Foundry

Train a base language model on a chat-completion task. The model catalog in Azure AI Foundry offers many open-source models that can be fine-tuned for your specific model behavior needs.

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7. Implement a responsible generative AI solution in Azure AI Foundry

Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.

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8. Evaluate generative AI performance in Azure AI Foundry portal

Evaluating copilots is essential to ensure your generative AI applications meet user needs, provide accurate responses, and continuously improve over time. Discover how to assess and optimize the performance of your generative AI applications using the tools and features available in the Azure AI Studio.

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