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Develop Generative AI Solutions with Azure OpenAI Service (AI-050)

Course 8680

  • Duration: 1 day
  • Language: English
  • Level: Intermediate

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 AI Solutions with Azure course, you'll learn how to provision Azure OpenAI service, deploy models, and use them in generative AI applications.

AI Solutions with Azure Delivery Methods

  • In-Person

  • Online

AI Solutions with Azure Training Information

In this course, you will learn how to:

  • Get to know the connection between artificial intelligence (AI), Responsible AI, and text, code, and image generation. 
  • Begin building an Azure OpenAI Service solution. 
  • Begin building apps that integrate with the Azure OpenAI Service. 
  • Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models' performance. 

Training Prerequisites

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. 

AI Solutions with Azure Training Outline

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

By the end of this module, you'll be able to:

  • Create an Azure OpenAI Service resource and understand the types of Azure OpenAI base models.
  • Use the Azure OpenAI Studio, console, or REST API to deploy and test a base model in the Studio's playgrounds.
  • Generate completions to prompts and begin to manage model parameters.

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

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
Get This Course 9 170 kr For Team Prices Call: +46 (0)8 506 668 00

  • 1-Day Instructor-Led Training

  • Hands-on Labs

  • Microsoft Official Content

  • After-Course Instructor Coaching

Get the Advantage 35 495 kr
  • Take this course and gain unlimited access to more than 300 virtual instructor-led courses
  • Future-proof your career with more than 100 sought-after certifications in the market
  • Build real skills through hands-on learning in more than 180 virtual labs
  • Grow your skills and capabilities with more than one course at a time and save
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  • nov 6 15:00 - 22:30 CET
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  • jan 29 9:00 - 16:30 CET
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  • mar 11 14:00 - 21:30 CET
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  • apr 8 15:00 - 22:30 CEST
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  • apr 29 9:00 - 16:30 CEST
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  • apr 29 10:00 - 18:00 CEST
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  • maj 13 15:00 - 22:30 CEST
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  • jun 10 15:00 - 22:30 CEST
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  • jul 3 15:00 - 22:30 CEST
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  • jul 29 10:00 - 18:00 CEST
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  • aug 5 15:00 - 22:30 CEST
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  • sep 9 15:00 - 22:30 CEST
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  • Bring this or any training to your organisation

  • Full-scale programme development

  • Delivered when, where, and how you want it

  • Blended learning models

  • Tailored content

  • Expert team coaching

Get the Advantage 35 495 kr
  • Take this course and gain unlimited access to more than 300 virtual instructor-led courses
  • Future-proof your career with more than 100 sought-after certifications in the market
  • Build real skills through hands-on learning in more than 180 virtual labs
  • Grow your skills and capabilities with more than one course at a time and save
Thank you for choosing subscriptions!
#8680
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AI Solutions with Azure FAQs

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.

We will be providing demonstrations of the labs; however, Azure OpenAI requires registration and approval of your Azure subscription, which can take several days for attendees to complete.

As demand for AI services increases, we worry that attendees will have a degraded experience if they cannot be approved in time for the class. Therefore, we will be demonstrating labs and welcome attendees to use their after-course instructor coaching for any troubles they encounter while performing the labs on their own after the class.

Azure OpenAI Service provides access to OpenAI's powerful large language models such as ChatGPT, GPT, Codex, and Embeddings models.

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.

Microsoft Azure AI engineers build, manage, and deploy AI solutions that make the most of Azure Cognitive Services and Azure services. Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, integration, maintenance, performance tuning, and monitoring.

These professionals work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, infrastructure administrators, and other software developers to build complete end-to-end AI solutions.

Azure AI engineers have experience developing solutions that use languages such as Python or C# and should be able to use REST-based APIs and software development kits (SDKs) to build secure image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure.

They should be familiar with all methods of implementing AI solutions. Plus, they understand the components that make up the Azure AI portfolio and the available data storage options. Azure AI engineers also need to understand and be able to apply responsible AI principles.

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