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Develop Generative AI Solutions with Azure OpenAI Service
Course Description
Overview
Azure OpenAI Service provides access to OpenAI's powerful large language models such as GPT; the model behind the popular ChatGPT service. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio. In this course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications.To complete the hands-on labs in this course, students require an Azure subscription that has been approved for access to the Azure OpenAI service. Access approval can take several days to be granted. See https://learn.microsoft.com/legal/cognitive-services/openai/limited-access for details.
Objectives
Audience
Prerequisites
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Before starting this learning path, you should already have:
- Familiarity with Azure and the Azure portal.
- Experience programming with C# or Python. If you have no previous programming experience, we recommend you complete the Take your first steps with C# or Take your first steps with Python learning path before taking this course.
Topics
- Introduction
- What is generative AI
- Describe Azure OpenAI
- How to use Azure OpenAI
- Understand OpenAI's natural language capabilities
- Understand OpenAI code generation capabilities
- Understand OpenAI's image generation capabilities
- Describe Azure OpenAI's access and responsible AI policies
- Exercise - Explore Azure OpenAI Service
- Knowledge check
- Introduction
- Access Azure OpenAI Service
- Use Azure OpenAI Studio
- Explore types of generative AI models
- Deploy generative AI models
- Use prompts to get completions from models
- Test models in Azure OpenAI Studio's playgrounds
- Exercise - Get started with Azure OpenAI Service
- Knowledge check
- Introduction
- Integrate Azure OpenAI into your app
- Use Azure OpenAI REST API
- Use Azure OpenAI SDK
- Exercise - Integrate Azure OpenAI into your app
- Knowledge check
- Introduction
- Understand prompt engineering
- Write more effective prompts
- Provide context to improve accuracy
- Exercise - Utilize prompt engineering in your application
- Knowledge check
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Self-Paced Training Info
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- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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