Overview
Develop Generative AI Solutions with Azure OpenAI Service
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.
Skills Covered
- Introduction to Azure OpenAI Service
- Get started with Azure OpenAI Service
- Build natural language solutions with Azure OpenAI Service
- Apply prompt engineering with Azure OpenAI Service
Who Should Attend
The audience for this course includes software developers and data scientists who need to use large language models for generative AI. Some programming experience is recommended, but the course will be valuable to anyone seeking to understand how the Azure OpenAI service can be used to implement generative AI solutions.
Job role: AI Engineer, Data Scientist
Course Curriculum
Prerequisites
There are no prerequisites required to attend this course.
Download Course Syllabus
Course Modules
Get to know the connection between artificial intelligence (AI), Responsible AI, and text, code, and image generation. Understand how you can use Azure OpenAI to build solutions against AI models within Azure.
Learning objectives
In this module you’ll learn how to:
- Describe Azure OpenAI workloads and access the Azure OpenAI Service
- Understand generative AI models
- Understand Azure OpenAI’s language, code, and image capabilities
- Understand Azure OpenAI’s responsible AI practices and limited access policies
Prerequisites
None
This module provides engineers with the skills to begin building an Azure OpenAI Service solution.
Learning objectives
By the end of this module, you’ll be able to:
- Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.
- Use the Azure OpenAI Studio, console, or REST API to deploy a base model and test it in the Studio’s playgrounds.
- Generate completions to prompts and begin to manage model parameters.
Prerequisites
- Familiarity with Azure and the Azure portal.
- An understanding of generative AI. You can learn more with Introduction to Azure OpenAI Service.
This module provides engineers with the skills to begin building apps that integrate with the Azure OpenAI Service.
Learning objectives
By the end of this module, you’ll be able to:
- Integrate Azure OpenAI into your application
- Differentiate between different endpoints available to your application
- Generate completions to prompts using the REST API and language specific SDKs
Prerequisites
- Familiarity with Azure and the Azure portal.
- An understanding of generative AI. You can learn more with Introduction to Azure OpenAI Service.
- 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 starting this one.
Prompt engineering in Azure OpenAI is a technique that involves designing prompts for natural language processing models. This process improves accuracy and relevancy in responses, optimizing the performance of the model.
Learning objectives
By the end of this module, you’ll be able to:
- Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models’ performance.
- Know how to design and optimize prompts to better utilize AI models.
- Include clear instructions, request output composition, and use contextual content to improve the quality of the model’s responses.
Prerequisites
- Familiarity with Azure and the Azure portal.
- An understanding of generative AI. You can learn more with Introduction to Azure OpenAI Service.
- 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 starting this one.
- Before starting this module, we recommend you complete the previous modules in the Develop AI solutions with Azure OpenAI learning path.
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Training Options
- ILT: Instructor-Led Training
- VILT: Virtual Instructor-Led Training
RM1,200.00Enroll Now
RM1,200.00Enroll Now
Exam & Certification
This course is not associated with any Certification.
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Frequently Asked Questions
Azure OpenAI Service provides REST API access to OpenAI’s powerful language models including the GPT-4, GPT-35-Turbo, and Embeddings model series. In addition, the new GPT-4 and gpt-35-turbo model series have now reached general availability. These models can be easily adapted to your specific task including but not limited to content generation, summarization, semantic search, and natural language to code translation. Users can access the service through REST APIs, Python SDK, or our web-based interface in the Azure OpenAI Studio.
Azure OpenAI Service gives customers advanced language AI with OpenAI GPT-4, GPT-3, Codex, and DALL-E models with the security and enterprise promise of Azure. Azure OpenAI co-develops the APIs with OpenAI, ensuring compatibility and a smooth transition from one to the other.
With Azure OpenAI, customers get the security capabilities of Microsoft Azure while running the same models as OpenAI. Azure OpenAI offers private networking, regional availability, and responsible AI content filtering.
Generative AI refers to a category of AI that uses systems called neural networks to analyze data, find patterns and use these patterns to generate or create a new output, such as text, photo, video, code, data, and more. Examples of how Microsoft is using generative AI include GitHub Copilot, the new Bing and Bing Chat experience, new Viva Sales and Dynamics 365 experiences, DALL-E in Designer and Bing Image Creator. We are also making this technology available to customers through the Azure OpenAI Service.
