Develop generative AI apps in Azure (AI-3016)
Embark on a transformative journey to harness the power of AI with our course, Develop Custom Copilots with Azure AI Studio. Designed with both individuals and companies in mind, this course offers an engaging introduction to Azure AI Studio’s capabilities, offering you the tools to leverage AI in dynamic and innovative ways. Whether you're looking to enhance your team's skills or embark on an individual learning path, this course is tailored to help you unlock the potential of Azure AI Studio.
The course begins with an introduction to Azure AI Studio, where you will explore what it is, understand its functionalities, and learn when to apply its use cases. This foundational knowledge prepares you for the next step, exploring and deploying models from the model catalog in Azure AI Studio. You’ll learn to navigate the language models, deploy models to endpoints, and improve model performance, equipping you with practical skills in model optimization and deployment.
As you advance, you'll get started with prompt flow, an important component for developing language model applications within Azure AI Studio. You'll gain insights into the development lifecycle of a large language model app, discovering core components, flow types, connections, and monitoring options. This understanding is further enhanced as you build a RAG-based copilot solution. Here, you’ll learn to integrate your data, making it searchable and using prompt flow to construct an effective copilot.
Integrate and fine-tune language models with your copilot to fully utilize Azure AI Studio's capabilities. This lesson guides you through deciding when to fine-tune, preparing data for a chat completion model, and exploring fine-tuning techniques, allowing you to tailor the models to your specific needs.
The course also covers evaluating the performance of your custom copilot within Azure AI Studio. Through this lesson, you'll assess model performance, conduct manual evaluations, and refine your copilot's efficacy, ensuring robust and reliable AI solutions.
Finally, you'll learn about responsible generative AI. Plan and operate a responsible AI solution by identifying, measuring, and mitigating potential harms. This lesson empowers you to ensure that your AI applications are ethical and socially responsible, aligning with industry standards and best practices.
Upon completion of the course, you will be adept at building and deploying custom copilots using Azure AI Studio, with skills in AI model integration, evaluation, and the implementation of responsible AI practices. This course is an essential stepping stone for advancing your enterprise’s AI capabilities or enhancing your personal expertise in the ever-evolving field of artificial intelligence.
- Understand Azure AI Foundry and its role in building AI solutions
- Explore and deploy models from the model catalog
- Use endpoints and optimize model performance
- Work with the Azure AI Foundry SDK to create AI apps
- Build chat clients and develop apps with prompt flow
- Connect to runtimes, explore variants, and monitor performance
- Ground language models with your data and make it searchable
- Create and implement RAG-based solutions in prompt flow
- Fine-tune language models and prepare datasets for tuning
- Plan and implement responsible AI solutions
- Identify, measure, and mitigate potential harms
- Assess, manually evaluate, and improve model performance
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private classes are delivered for groups at your offices or a location of your choice.
Webucator is a Microsoft Certified Partner. This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
- Plan and prepare to develop AI solutions on Azure
- What is AI?
- Azure AI services
- Azure AI Foundry
- Developer tools and SDKs
- Responsible AI
- Choose and deploy models from the model catalog in Azure AI Foundry portal
- Explore the model catalog
- Deploy a model to an endpoint
- Optimize model performance
- Develop an AI app with the Azure AI Foundry SDK
- What is the Azure AI Foundry SDK?
- Work with project connections
- Create a chat client
- Get started with prompt flow to develop language model apps in the Azure AI Foundry
- Understand the development lifecycle of a large language model (LLM) app
- Understand core components and explore flow types
- Explore connections and runtimes
- Explore variants and monitoring options
- Develop a RAG-based solution with your own data using Azure AI Foundry
- Understand how to ground your language model
- Make your data searchable
- Create a RAG-based client application
- Implement RAG in a prompt flow
- Fine-tune a language model with Azure AI Foundry
- Understand when to fine-tune a language model
- Prepare your data to fine-tune a chat completion model
- Explore fine-tuning language models in Azure AI Foundry portal
- Implement a responsible generative AI solution in Azure AI Foundry
- Plan a responsible generative AI solution
- Map potential harms
- Measure potential harms
- Mitigate potential harms
- Manage a responsible generative AI solution
- Evaluate generative AI performance in Azure AI Foundry portal
- Assess the model performance
- Manually evaluate the performance of a model
- Automated evaluations
Each student will receive a comprehensive set of materials, including course notes and all the class examples.
Experience in the following is required for this Copilot class:
Before starting this course, you should be familiar with fundamental AI concepts and services in Azure, especially Azure AI Foundry.
Live Public Class
$681.10 / student
Live Private Class
- Private Class for your Team
- Live training
- Online or On-location
- Customizable
- Expert Instructors