AI-103T00: Develop AI Apps and Agents on Azure

This course is intended for software developers wanting to build AI infused applications that leverage Microsoft Foundry. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement knowledge connections or tools in your agentic applications. This course also covers multimodal capabilities and understanding of complex content.

Description

1 - Plan and prepare to develop AI solutions on Azure

  • What is AI?
  • Microsoft Foundry
  • Foundry Tools
  • Developer tools and SDKs
  • Responsible AI
  • Module assessment

2 - Select, deploy, and evaluate Microsoft Foundry models

  • Explore the model catalog
  • Select models using benchmarks
  • Deploy models to endpoints
  • Evaluate model performance

3 - Develop a generative AI chat app with Microsoft Foundry

  • Explore with the model playground
  • Choose an endpoint and SDK
  • Generate responses with the Responses API
  • Generate responses with the ChatCompletions API

4 - Develop generative AI apps that use tools

  • What are tools?
  • Use the code_interpreter tool
  • Use the web_search tool
  • Use the file_search tool
  • Use the functions tool
  • Module assessment

5 - Optimize generative AI model performance with Microsoft Foundry

  • Optimize model output with prompt engineering
  • Ground your model with Retrieval Augmented Generation
  • Fine-tune a model for consistent behavior
  • Compare and combine optimization strategies
  • Module assessment

6 - Implement a responsible generative AI solution in Microsoft Foundry

  • Plan a responsible generative AI solution
  • Map potential harms
  • Measure potential harms
  • Mitigate potential harms
  • Manage a responsible generative AI solution
  • Module assessment

7 - Develop AI agents with Microsoft Foundry and Visual Studio Code

  • Understand AI agents and Microsoft Foundry Agent Service
  • Explore development approaches
  • Build your first agent in Microsoft Foundry
  • Set up Visual Studio Code for agent development
  • Configure and manage agents in Visual Studio Code
  • Extend agent capabilities with tools
  • Test, deploy, and integrate agents

8 - Integrate custom tools into your agent

  • Why use custom tools
  • Options for implementing custom tools
  • How to integrate custom tools
  • Module assessment

9 - Integrate MCP Tools with Azure AI Agents

  • Understand MCP tool discovery
  • Integrate agent tools using an MCP server and client
  • Use Azure AI agents with MCP servers
  • Module assessment

10 - Build knowledge-enhanced AI agents with Foundry IQ

  • Understanding RAG for agents
  • Explore Foundry IQ
  • Configure data sources for knowledge bases
  • Configure retrieval with Foundry IQ

11 - Integrate your agent with Microsoft 365

  • Understand Foundry agent publishing options
  • Publish an agent from Foundry portal to Teams
  • Advanced - Use Microsoft 365 Agents Toolkit
  • Access Microsoft 365 data with Work IQ
  • Test and iterate your integrated agent

12 - Build agent-driven workflows using Microsoft Foundry

  • Understand Workflows
  • Identify Workflow Patterns
  • Create workflows in Microsoft Foundry
  • Add Agents to a Workflow
  • Apply Power Fx in Workflows
  • Maintain Workflows in Microsoft Foundry
  • Use workflows in code
  • Module Assessment

13 - Develop an AI agent with Microsoft Agent Framework

  • Understand Microsoft Agent Framework AI agents
  • Create an Azure AI agent with Microsoft Agent Framework
  • Add tools to Azure AI agent

14 - Orchestrate a multi-agent solution using the Microsoft Agent Framework

  • Understand the Microsoft Agent Framework
  • Understand agent orchestration
  • Use concurrent orchestration
  • Use sequential orchestration
  • Use group chat orchestration
  • Use handoff orchestration
  • Use Magentic orchestration

15 - Discover Azure AI Agents with A2A

  • Define an A2A agent
  • Implement an agent executor
  • Host an A2A server
  • Connect to your A2A agent
  • Module assessment

16 - Analyze text with Azure Language in Foundry Tools

  • Azure Language in Microsoft Foundry Tools
  • Detect language
  • Extract entities
  • Extract personally identifiable information (PII)
  • Module assessment

17 - Develop a text analysis agent with the Azure Language MCP server

  • Understand the Azure Language MCP server
  • Connect and use the Language MCP server with an agent

18 - Develop a speech-capable generative AI application

  • Choose a speech-capable model
  • Transcribe speech
  • Synthesize speech
  • Module assessment

19 - Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools

  • Azure Speech in Foundry Tools
  • Use the Speech to Text API
  • Use the Text to Speech API
  • Configure audio format and voices
  • Use Speech Synthesis Markup Language
  • Module assessment

20 - Develop a speech agent with the Azure Speech MCP server

  • Understand the Azure Speech MCP server
  • Connect and use the Speech MCP server with an agent

21 - Develop an Azure Speech Voice Live Agent in Microsoft Foundry

  • Explore the Azure Voice Live API
  • Explore the AI Voice Live client library for Python
  • Create a Voice Live agent
  • Module assessment

22 - Translate text and speech with Microsoft Foundry Tools

  • Translation in Microsoft Foundry
  • Translate text
  • Translate speech
  • Module assessment

23 - Develop a vision-enabled generative AI application

  • Use a vision-capable model in the Microsoft Foundry portal
  • Develop a vision-based chat app
  • Module assessment

24 - Generate images with AI

  • What are image-generation models?
  • Explore image-generation models in Microsoft Foundry portal
  • Create a client application that uses an image generation model
  • Module assessment

25 - Generate videos with Microsoft Foundry

  • Deploy a video generating model
  • Generate video from a prompt
  • Generate video in Python
  • Module assessment

26 - Analyze images with Content Understanding

  • What is Content Understanding?
  • Analyze images with Content Understanding
  • Module assessment

27 - Create a multimodal analysis solution with Azure Content Understanding

  • What is Azure Content Understanding?
  • Create a Content Understanding analyzer
  • Use the Content Understanding API
  • Module assessment

28 - Create an Azure Content Understanding client application

  • Prepare to use the AI Content Understanding API
  • Create a Content Understanding analyzer
  • Analyze content
  • Module assessment

29 - Extract data with Azure Document Intelligence

  • What is Azure Document Intelligence?
  • Use the Document Intelligence Studio
  • Use prebuilt models
  • Train and use custom models
  • Module assessment

30 - Create a knowledge mining solution with Azure AI Search

  • What is Azure AI Search?
  • Extract data with an indexer
  • Enrich extracted data with AI skills
  • Search an index
  • Persist extracted information in a knowledge store
  • Module assessment

Target Audience

This course was designed for software engineers concerned with building, managing and deploying AI solutions that leverage Microsoft Foundry. They are familiar with Python and have knowledge on using APIs and SDKs to build agents and generative AI solutions on Azure.

Similar events

This three-day, instructor-led course provides IS auditors with the foundational knowledge and background of AI solutions to evaluate their proper governance, design, development, and security to apply their expertise in audit and assurance activities in the enterprise. The course is structured to align with the job practice and features a variety of knowledge check questions, case studies, activities, and discussions designed to apply the concepts to real-life business scenarios.

More Information

ISACA Advanced in AI Security ManagementTM (AAISM) validates security management professionals’ ability to demonstrate their expertise in AI. This credential builds upon existing security best practices to enhance expertise and adapt to the evolving AI-driven landscape, ensuring robust protection and a strategic edge.

More Information

Artificial intelligence (AI) is not just another technology or process for the business to consider; it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward.

More Information

The AI Fundamentals and AI Hacking 101 ILT teaches students the fundamentals of how AI works under the hood and then how to break it. The first day of the course focuses on the fundamentals of how AI works. Students will learn and perform labs on topics such as: How do neural networks function Training of neural networks The progression of AI for natural language processing Recurrent neural networks (RNN) Large Language Models and Attention Self-Hosting LLMs and interacting with them programmatically The hacking portion of the course focuses on penetration testing AI/LLM based applications such as customer facing chatbots by demonstrating how to detect and exploit common AI vulnerabilities such as: Prompt Injection Sensitive Information Disclosure Improper Output Handling System Prompt Leakage Misinformation Excessive Agency Not only will students learn about these core topics and exploits, but they will also spend hands-on time in a custom-built environment training their own neural networks, tweaking LLMs, exploiting and uncovering vulnerabilities and much more. The online lab features the TCM Vulnerable Chatbot, a customer service chatbot that can interact with customers' tickets and improve its responses via Retrieval Augmented Generation (RAG) using the company's knowledge base.

More Information

The AI Hacking 101 ILT teaches students the fundamentals of penetration testing AI/LLM based applications such as customer facing chatbots. The course focuses on demonstrating how to detect and exploit common AI vulnerabilities such as: Prompt Injection Sensitive Information Disclosure Improper Output Handling System Prompt Leakage Misinformation Excessive Agency Not only will students learn about these exploits, but they will also spend hands-on time in a custom-built environment exploiting and uncovering these vulnerabilities. The online lab features the TCM Vulnerable Chatbot, a customer service chatbot that can interact with customers' tickets and improve its responses via Retrieval Augmented Generation (RAG) using the company's knowledge base.

More Information

In audio, video, image, gaming, and other media production industries, artificial intelligence (AI) has been a truly disruptive force—enabling a higher level of results in a fraction of the time. The rapid pace at which AI is growing can be overwhelming, and fears of AI tools replacing human workforces are growing. This course is designed to help media professionals understand the basics of AI and leverage the assistive and generative AI tools available to create high-quality productions and production assets. It will give you the essential knowledge of AI you'll need to remain competitive, productive, and relevant in these fast-paced and exciting times. This course is created by Be Licensed in partnership with CertNexus (a division of Logical Operations). It is also designed to assist students in preparing for the CertNexus® AI Technologies in Media (Exam AIM-110) credential.

More Information

AI-102: Develop AI solutions in Azure is intended for software developers wanting to build AI infused applications that leverage Azure AI Foundry and other Azure AI services. Topics in this course include developing generative AI apps, building AI agents, and solutions that implement computer vision and information extraction.

More Information

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.

More Information

This 1-day course focuses on building intelligent applications that can see, interpret, and reason over images and documents using different multimodal models and agent-based tools. Learners explore how visual and document inputs can be combined with language models to enable structured extraction, analysis, and decision-making workflows. The course emphasizes practical patterns for extracting information, orchestrating tools, and grounding model responses in visual data.

More Information

This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalable AI infrastructure, managing the full lifecycle of traditional machine learning models with Azure Machine Learning, and deploying, evaluating, monitoring, and optimizing generative AI applications and agents using Microsoft Foundry. Learners will gain hands-on knowledge of automation, continuous integration and delivery, infrastructure as code, and observability by using tools such as GitHub Actions, Azure CLI, and Bicep. The course emphasizes collaboration with data science and DevOps teams to deliver reliable, production-ready AI systems aligned with modern MLOps and GenAIOps best practices.

More Information

Generative Artificial Intelligence (AI) is becoming more accessible through easy-to-use platforms like Azure AI Studio. Learn how to build generative AI applications like custom copilots that use language models and prompt flow to provide value to your users.

More Information

This learning path explores how the Azure AI and Azure Machine Learning Services integrations provided by the Azure AI extension for Azure Database for PostgreSQL - Flexible Server can enable you to build AI-powered apps.

More Information

Do you have information locked up in structured and unstructured data sources? Using Azure AI Search, you can extract key insights from this data, and enable applications to search and analyze them.

More Information

Get more done and unleash your creativity with Microsoft Copilot. In this learning path, you'll explore how to use Microsoft Copilot to help you research, find information, and generate effective content.

More Information

Generative Artificial Intelligence (AI) is becoming more functional and accessible, and AI agents are a key component of this evolution. This learning path will help you understand the AI agents, including when to use them and how to build them, using Azure AI Agent Service and Semantic Kernel Agent Framework. By the end of this learning path, you will have the skills needed to develop AI agents on Azure.

More Information

This course introduces fundamental concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. It teaches a mix of AI concepts and technology skills that are considered foundational to a successful career implementing AI solutions on Microsoft Azure.

More Information

Learn how to use the Semantic Kernel SDK to build intelligent applications that automate tasks and perform natural language processing.

More Information

Artificial intelligence (AI) and machine learning (ML) have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands on activities for each topic area.

More Information

This course is designed for business users, business leaders, and decision makers who want to understand the transformative potential of generative AI and its impact on their organizations. You'll gain a comprehensive understanding of this technology, learn how it can be leveraged to drive innovation and efficiency, and explore the range of generative AI services available on Google Cloud. By the end of this course, you'll be equipped to make informed decisions about implementing AI solutions.

More Information

A major milestone in business automation has been reached—generative AI. Despite its recency, it has already started having a significant impact on our lives. But, the rapid pace at which generative AI is growing can be overwhelming. And, there are so many facets to this field that it can be difficult to know how to use it effectively to improve the business. This course is designed to demystify generative AI for business professionals, as well as to trace its power to actionable, real-world business goals. It will give you the essential knowledge of generative AI you'll need to elevate the organization in these exciting times.

More Information

As generative AI becomes more common, the ability to interact with large language models is shifting from niche knowledge to a necessary skill across many different industries and roles. In this course, you will learn the fundamentals of prompting large language models and exploring further techniques for improving the output from large language models.

More Information