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1) Get started with Azure OpenAI Service

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.

Link: https://learn.microsoft.com/en-us/training/modules/get-started-openai/
Cost: Free
Time: 40 Minutes

2) 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

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.

Link: https://learn.microsoft.com/en-us/training/modules/apply-prompt-engineering-azure-openai/
Cost: Free
Time: 1 Hour

3) Generate code with Azure OpenAI Service

This module shows engineers how to use the Azure OpenAI Service to generate and improve code.

Learning objectives

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

• Use natural language prompts to write code

• Build unit tests and understand complex code with AI models

• Generate comments and documentation for existing code

Link: https://learn.microsoft.com/en-us/training/modules/generate-code-azure-openai/
Cost: Free
Time: 50 Minutes

4) Generate images with Azure OpenAI Service

The Azure OpenAI service includes the DALL-E model, which you can use to generate original images based on natural language prompts.

Learning objectives

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

• Describe the capabilities of DALL-E in the Azure openAI service

• Use the DALL-E playground in Azure OpenAI Studio

• Use the Azure OpenAI REST interface to integrate DALL-E image generation into your apps

Link: https://learn.microsoft.com/en-us/training/modules/generate-images-azure-openai/
Cost: Free
Time: 40 Minutes

5) Fundamentals of Responsible Generative AI

Generative AI enables amazing creative solutions, but must be implemented responsibly to minimize the risk of harmful content generation.

Learning objectives

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

• Describe an overall process for responsible generative AI solution development

• Identify and prioritize potential harms relevant to a generative AI solution

• Measure the presence of harms in a generative AI solution

• Mitigate harms in a generative AI solution

• Prepare to deploy and operate a generative AI solution responsibly

Link: https://learn.microsoft.com/en-us/training/modules/responsible-generative-ai/
Cost: Free
Time: 50 Minutes

6) Create question answering solutions with Azure AI Language

The question answering capability of the Azure AI Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.

Learning objectives

After completing this module, you will be able to:

• Understand question answering and how it compares to language understanding.

• Create, test, publish, and consume a knowledge base.

• Implement multi-turn conversation and active learning.

• Create a question answering bot to interact with using natural language.

Link: https://learn.microsoft.com/en-us/training/modules/create-question-answer-solution-ai-language/
Cost: Free
Time: 45 Minutes

7) Build a conversational language understanding model

The Azure AI Language conversational language understanding service (CLU) enables you to train a model that apps can use to extract meaning from natural language.

Learning objectives

After completing this module, you'll be able to:

• Provision Azure resources for Azure AI Language resource

• Define intents, utterances, and entities

• Use patterns to differentiate similar utterances

• Use pre-built entity components

• Train, test, publish, and review an Azure AI Language model

Link: https://learn.microsoft.com/en-us/training/modules/build-language-understanding-model/
Cost: Free
Time: 1 Hour

8) Create a custom text classification solution

The Azure AI Language service enables processing of natural language to use in your own app. Learn how to build a custom text classification project.

Learning objectives

After completing this module, you'll be able to:

• Understand types of classification projects

• Build a custom text classification project

• Tag data, train, and deploy a model

• Submit classification tasks from your own app

Link: https://learn.microsoft.com/en-us/training/modules/custom-text-classification/
Cost: Free
Time: 40 Minutes

9) Manage topics in Microsoft Copilot Studio

In Microsoft Copilot Studio, topics are used to small conversations related to a specific subject. A Microsoft Copilot Studio bot typically includes many topics. This module you're introduced to the basic principles of topics such as trigger phrases and conversation paths and how to create them.

Learning objectives

This module explains how to:

• Use topics to create and manage conversation paths in a bot.

• Work with topic triggers and conversation nodes.

• Add branching to a topic.

• Use system topics and create topics from content.

• Set up fall-back topics to handle unrecognized user input.

Link: https://learn.microsoft.com/en-us/training/modules/manage-power-virtual-agents-topics/
Cost: Free
Time: 55 Minutes

10) Build effective copilots with Microsoft Copilot Studio

In this module, you'll learn about some design principles and best practices that you can use when designing copilots with Microsoft Copilot Studio.

Learning objectives

In this module, you'll:

• Examine techniques for planning copilots.

• Explore design elements for creating successful copilots.

• Review the different conversation types and why they're important.

• Examine best practices for creating good trigger phrases.

• Explore different techniques for building conversational copilots.

• Review how to use analytics to improve your copilot performance.

Link: https://learn.microsoft.com/en-us/training/modules/build-effective-bots/
Cost: Free
Time: 55 Minutes

Bonus: Get started with Azure AI Services

Azure AI Services is a collection of services that are building blocks of AI functionality you can integrate into your applications. In this learning path, you'll learn how to provision, secure, monitor, and deploy Azure AI Services resources and use them to build intelligent solutions.

Prerequisites

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 starting this one.

Link: https://learn.microsoft.com/en-us/training/paths/get-started-azure-ai/
Cost: Free
Time: 55 Minutes

For Beginners:

10 FREE Courses on AI with Microsoft for Beginners in 2024

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