How internal solutions are built on top of OpenAI’s models? How can modern AI be integrated into organisation’s systems and applications? The new Microsoft course AI-050 focuses specifically on these topics!
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.
You will learn how to use the Azure OpenAI service, deploy its models, and apply them in AI applications, such as an internal ChatGPT for your company.
Upcoming trainings in English
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Implementation: Online
Length: 1 day
Material: Microsoft English Material (MOC)
Audience profileThe 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.
Module 1: Introduction to Azure OpenAI Service
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:
- 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
Module 2: Get started with Azure OpenAI Service
This module provides engineers with the skills to begin building an Azure OpenAI Service solution.
Learning objectives:
- 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.
Module 3: Build natural language solutions with Azure OpenAI Service
This module provides engineers with the skills to begin building apps that integrate with the Azure OpenAI Service.
Learning objectives:
- 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
Module 4: Apply prompt engineering with Azure OpenAI Service
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:
- 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.
