{"id":253301,"date":"2026-04-09T00:14:51","date_gmt":"2026-04-08T22:14:51","guid":{"rendered":"https:\/\/www.itta.net\/?post_type=formations&#038;p=253301"},"modified":"2026-05-20T11:38:34","modified_gmt":"2026-05-20T09:38:34","slug":"develop-ai-apps-and-agents-on-azure-ai-103","status":"publish","type":"formations","link":"https:\/\/www.itta.net\/en\/formations\/develop-ai-apps-and-agents-on-azure-ai-103\/","title":{"rendered":"Develop AI apps and agents on Azure (AI-103)"},"content":{"rendered":"<p>Building AI applications and agents in Azure has never been more accessible. The AI-103 training guides you through the Azure AI Foundry platform to develop, deploy and operate generative and conventional AI solutions in production environments.<\/p>\n<p>In four days, you work on AI agent orchestration, GPT and Azure OpenAI model integration, Retrieval Augmented Generation (RAG) with Azure AI Search, and Azure cognitive AI services: language, vision, document intelligence, speech. The training is delivered in Geneva and Lausanne by a Microsoft Certified Trainer.<\/p>\n","protected":false},"featured_media":0,"parent":0,"menu_order":0,"template":"","editeurs":[4277,1335],"domaine":[4244,2980,4272],"class_list":["post-253301","formations","type-formations","status-publish","hentry","editeurs-azure-ai-services","editeurs-microsoft","domaine-developpement-ia-et-llm","domaine-intelligence-artificielle","domaine-plateformes-ia-azure"],"acf":{"reference":"AI-103T00","duree_nombre":4,"duree_unite":"jour","prix_virtuel":3000,"prix_presentiel":3200,"prix_blended":"","prix_elearning":"","views":29,"niveau":["Interm\u00e9diaire"],"role":[],"certifiant":["Certifiant"],"pdus":"","lieux":["Gen\u00e8ve","Lausanne"],"formats_dapprentissage":["presentiel","virtuel"],"examen_inclus":"Optionnel","garanti":[],"financement":["Temptraining"],"description_temptraining":"","description_caf":"","description_title":"Develop AI apps and agents on Azure Training (AI-103)","objectifs":"<ul>\n<li>Design and deploy AI applications in Azure AI Foundry with GPT and Azure OpenAI models<\/li>\n<li>Build AI agents orchestrating multiple tools and data sources<\/li>\n<li>Implement Retrieval Augmented Generation (RAG) with Azure AI Search to ground models on your data<\/li>\n<li>Integrate Azure AI Language, Vision, Document Intelligence and Speech services in your applications<\/li>\n<li>Secure and monitor production AI solutions with content safety and responsible AI<\/li>\n<\/ul>","connaissances":"","profils_participants":"","examen":"<p>This course prepares you to the AI-102: Designing and Implementing a Microsoft Azure AI Solution exam.<\/p>","documentation":"","lab__exercices":"","contenu_cours":"<p><strong>Module 1 : Plan and prepare to develop AI solutions on Azure<\/strong><\/p>\n<ul>\n<li>What is AI?<\/li>\n<li>Microsoft Foundry<\/li>\n<li>Foundry Tools<\/li>\n<li>Developer tools and SDKs<\/li>\n<li>Responsible AI<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 2 : Select, deploy, and evaluate Microsoft Foundry models<\/strong><\/p>\n<ul>\n<li>Explore the model catalog<\/li>\n<li>Select models using benchmarks<\/li>\n<li>Deploy models to endpoints<\/li>\n<li>Evaluate model performance<\/li>\n<\/ul>\n<p><strong>Module 3 : Develop a generative AI chat app with Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Explore with the model playground<\/li>\n<li>Choose an endpoint and SDK<\/li>\n<li>Generate responses with the Responses API<\/li>\n<li>Generate responses with the ChatCompletions API<\/li>\n<\/ul>\n<p><strong>Module 4 : Develop generative AI apps that use tools<\/strong><\/p>\n<ul>\n<li>What are tools?<\/li>\n<li>Use the code_interpreter tool<\/li>\n<li>Use the web_search tool<\/li>\n<li>Use the file_search tool<\/li>\n<li>Use the function tool<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 5 : Optimize generative AI model performance with Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Optimize model output with prompt engineering<\/li>\n<li>Ground your model with Retrieval Augmented Generation<\/li>\n<li>Fine-tune a model for consistent behavior<\/li>\n<li>Compare and combine optimization strategies<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 6 : Implement a responsible generative AI solution in Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Plan a responsible generative AI solution<\/li>\n<li>Map potential harms<\/li>\n<li>Measure potential harms<\/li>\n<li>Mitigate potential harms<\/li>\n<li>Manage a responsible generative AI solution<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 7 : Develop AI agents with Microsoft Foundry and Visual Studio Code<\/strong><\/p>\n<ul>\n<li>Understand AI agents and Microsoft Foundry Agent Service<\/li>\n<li>Explore development approaches<\/li>\n<li>Build your first agent in Microsoft Foundry<\/li>\n<li>Set up Visual Studio Code for agent development<\/li>\n<li>Configure and manage agents in Visual Studio Code<\/li>\n<li>Extend agent capabilities with tools<\/li>\n<li>Test, deploy, and integrate agents<\/li>\n<\/ul>\n<p><strong>Module 8 : Integrate custom tools into your agent<\/strong><\/p>\n<ul>\n<li>Why use custom tools<\/li>\n<li>Options for implementing custom tools<\/li>\n<li>How to integrate custom tools<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 9 : Integrate MCP Tools with Azure AI Agents<\/strong><\/p>\n<ul>\n<li>Understand MCP tool discovery<\/li>\n<li>Integrate agent tools using an MCP server and client<\/li>\n<li>Use Azure AI agents with MCP servers<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 10 : Build knowledge-enhanced AI agents with Foundry IQ<\/strong><\/p>\n<ul>\n<li>Understanding RAG for agents<\/li>\n<li>Explore Foundry IQ<\/li>\n<li>Configure data sources for knowledge bases<\/li>\n<li>Configure retrieval with Foundry IQ<\/li>\n<\/ul>\n<p><strong>Module 11 : Integrate your agent with Microsoft 365<\/strong><\/p>\n<ul>\n<li>Understand Foundry agent publishing options<\/li>\n<li>Publish an agent from Foundry portal to Teams<\/li>\n<li>Advanced - Use Microsoft 365 Agents Toolkit<\/li>\n<li>Access Microsoft 365 data with Work IQ<\/li>\n<li>Test and iterate your integrated agent<\/li>\n<\/ul>\n<p><strong>Module 12 : Build agent-driven workflows using Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Understand Workflows<\/li>\n<li>Identify Workflow Patterns<\/li>\n<li>Create workflows in Microsoft Foundry<\/li>\n<li>Add Agents to a Workflow<\/li>\n<li>Apply Power Fx in Workflows<\/li>\n<li>Maintain Workflows in Microsoft Foundry<\/li>\n<li>Use workflows in code<\/li>\n<li>Module Assessment<\/li>\n<\/ul>\n<p><strong>Module 13 : Develop an AI agent with Microsoft Agent Framework<\/strong><\/p>\n<ul>\n<li>Understand Microsoft Agent Framework AI agents<\/li>\n<li>Create an Azure AI agent with Microsoft Agent Framework<\/li>\n<li>Add tools to Azure AI agent<\/li>\n<\/ul>\n<p><strong>Module 14 : Orchestrate a multi-agent solution using the Microsoft Agent Framework<\/strong><\/p>\n<ul>\n<li>Understand the Microsoft Agent Framework<\/li>\n<li>Understand agent orchestration<\/li>\n<li>Use concurrent orchestration<\/li>\n<li>Use sequential orchestration<\/li>\n<li>Use group chat orchestration<\/li>\n<li>Use handoff orchestration<\/li>\n<li>Use Magentic orchestration<\/li>\n<\/ul>\n<p><strong>Module 15 : Discover Azure AI Agents with A2A<\/strong><\/p>\n<ul>\n<li>Define an A2A agent<\/li>\n<li>Implement an agent executor<\/li>\n<li>Host an A2A server<\/li>\n<li>Connect to your A2A agent<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 16 : Analyze text with Azure Language in Foundry Tools<\/strong><\/p>\n<ul>\n<li>Azure Language in Microsoft Foundry Tools<\/li>\n<li>Detect language<\/li>\n<li>Extract entities<\/li>\n<li>Extract personally identifiable information (PII)<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 17 : Develop a text analysis agent with the Azure Language MCP server<\/strong><\/p>\n<ul>\n<li>Understand the Azure Language MCP server<\/li>\n<li>Connect and use the Language MCP server with an agent<\/li>\n<\/ul>\n<p><strong>Module 18 : Develop a speech-capable generative AI application<\/strong><\/p>\n<ul>\n<li>Choose a speech-capable model<\/li>\n<li>Transcribe speech<\/li>\n<li>Synthesize speech<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 19 : Create speech-enabled apps with Azure Speech in Microsoft Foundry Tools<\/strong><\/p>\n<ul>\n<li>Azure Speech in Foundry Tools<\/li>\n<li>Use the Speech to Text API<\/li>\n<li>Use the Text to Speech API<\/li>\n<li>Configure audio format and voices<\/li>\n<li>Use Speech Synthesis Markup Language<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 20 : Develop a speech agent with the Azure Speech MCP server<\/strong><\/p>\n<ul>\n<li>Understand the Azure Speech MCP server<\/li>\n<li>Connect and use the Speech MCP server with an agent<\/li>\n<\/ul>\n<p><strong>Module 21 : Develop an Azure Speech Voice Live Agent in Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Explore the Azure Voice Live API<\/li>\n<li>Explore the AI Voice Live client library for Python<\/li>\n<li>Create a Voice Live agent<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 22 : Translate text and speech with Microsoft Foundry Tools<\/strong><\/p>\n<ul>\n<li>Translation in Microsoft Foundry<\/li>\n<li>Translate text<\/li>\n<li>Translate speech<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 23 : Develop a vision-enabled generative AI application<\/strong><\/p>\n<ul>\n<li>Use a vision-capable model in the Microsoft Foundry portal<\/li>\n<li>Develop a vision-based chat app<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 24 : Generate images with AI<\/strong><\/p>\n<ul>\n<li>What are image-generation models?<\/li>\n<li>Explore image-generation models in Microsoft Foundry portal<\/li>\n<li>Create a client application that uses an image generation model<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 25 : Generate videos with Microsoft Foundry<\/strong><\/p>\n<ul>\n<li>Deploy a video generating model<\/li>\n<li>Generate video from a prompt<\/li>\n<li>Generate video in Python<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 26 : Analyze images with Content Understanding<\/strong><\/p>\n<ul>\n<li>What is Content Understanding?<\/li>\n<li>Analyze images with Content Understanding<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 27 : Create a multimodal analysis solution with Azure Content Understanding<\/strong><\/p>\n<ul>\n<li>What is Azure Content Understanding?<\/li>\n<li>Create a Content Understanding analyzer<\/li>\n<li>Use the Content Understanding API<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 28 : Create an Azure Content Understanding client application<\/strong><\/p>\n<ul>\n<li>Prepare to use the AI Content Understanding API<\/li>\n<li>Create a Content Understanding analyzer<\/li>\n<li>Analyze content<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 29 : Extract data with Azure Document Intelligence<\/strong><\/p>\n<ul>\n<li>What is Azure Document Intelligence?<\/li>\n<li>Use the Document Intelligence Studio<\/li>\n<li>Use prebuilt models<\/li>\n<li>Train and use custom models<\/li>\n<li>Module assessment<\/li>\n<\/ul>\n<p><strong>Module 30 : Create a knowledge mining solution with Azure AI Search<\/strong><\/p>\n<ul>\n<li>What is Azure AI Search?<\/li>\n<li>Extract data with an indexer<\/li>\n<li>Enrich extracted data with AI skills<\/li>\n<li>Search an index<\/li>\n<li>Persist extracted information in a knowledge store<\/li>\n<li>Module assessment<\/li>\n<\/ul>","cours_recommandes":null,"infos_additionnelles":"<h3>Azure AI Foundry: the central hub for AI development in Azure<\/h3>\n<p>Azure AI Foundry (formerly Azure AI Studio) is the unified environment that consolidates AI application development in the Microsoft ecosystem. The Develop AI apps and agents on Azure (AI-103) training covers project creation, model deployment, response evaluation and production deployment. You work on essential tools: prompt flow to orchestrate prompt chains, model catalog to explore GPT-4o, Phi, Mistral and open source models, and the playground for interactive testing.<\/p>\n\n<h3>Building AI agents in Azure<\/h3>\n<p>AI agents are at the heart of the program. You learn to design agents capable of using external tools (function calling), reasoning on multi-step plans, and interacting with structured and unstructured data sources. The program covers Azure AI Agent Service and design patterns (planner \/ executor, multi-agent collaboration, tool routing) that structure production agentic architectures.<\/p>\n\n<h3>Retrieval Augmented Generation (RAG) with Azure AI Search<\/h3>\n<p>RAG has become the standard pattern to ground generative models on enterprise data. The AI-103 training has you build a complete RAG pipeline: document ingestion, chunking, embedding generation with Azure OpenAI, vector indexing in Azure AI Search, hybrid search (vector + BM25), reranking and final generation by the LLM. You also address advanced techniques: query rewriting, multi-stage retrieval, contextual compression.<\/p>\n\n<h3>Azure AI services: language, vision, document, speech<\/h3>\n<p>Beyond generative AI, the training covers specialized Azure AI services: Azure AI Language (entity extraction, sentiment analysis, classification, QA), Azure AI Vision (OCR, object detection, image analysis), Azure AI Document Intelligence (structured document parsing, invoices, forms), Azure AI Speech (voice recognition, synthesis, translation). The goal is to combine these building blocks to build hybrid AI applications.<\/p>\n\n<h3>Security and responsible AI<\/h3>\n<p>The program integrates security and responsible AI concerns. You configure Azure AI Content Safety to filter harmful content, set up prompt and response monitoring, and apply the Microsoft Responsible AI Standard principles. Topics of prompt injection, jailbreak, data leakage and model bias are covered with associated countermeasures.<\/p>\n\n<h3>Audience and prerequisites<\/h3>\n<p>The Develop AI apps and agents on Azure (AI-103) training targets developers, data engineers and solution architects who build AI applications in Azure. Python or .NET development experience is required. Basic Azure knowledge (equivalent to AZ-900) and AI concepts (equivalent to AI-900) are recommended.<\/p>\n\n<h3>Microsoft Certified: Azure AI Engineer Associate exam<\/h3>\n<p>The AI-103 course prepares you for the <strong>AI-102: Designing and Implementing a Microsoft Azure AI Solution<\/strong> exam, which leads to the Microsoft Certified: Azure AI Engineer Associate certification. Note: AI-102 succeeds the previous program and AI-103 represents the evolution of the training course around agents and generative AI.<\/p>\n\n<h3>FAQ Develop AI apps and agents on Azure (AI-103)<\/h3>\n<p><strong>What's the difference between AI-103 and AI-102?<\/strong><\/p>\n<p>AI-102 is the Microsoft certification exam. AI-103 is the code of the training course preparing for this exam. The AI-103 content has been updated to integrate Azure AI Foundry, agents and RAG, topics now dominant in the exam program.<\/p>\n\n<p><strong>Do I need to know Python to take the training?<\/strong><\/p>\n<p>Yes, Python experience is strongly recommended. Azure AI SDKs are available in Python and .NET, but most examples use Python. Familiarity with Jupyter notebooks and REST API calls is a plus.<\/p>\n\n<p><strong>Does the AI-103 course include Azure OpenAI Service?<\/strong><\/p>\n<p>Yes, Azure OpenAI is central: GPT-4o, GPT-4 Turbo, text-embedding-3 embeddings, DALL-E. You work on deployment, fine-tuning, content filters and quotas \/ rate limits.<\/p>\n\n<p><strong>What jobs lead to the Azure AI Engineer Associate certification?<\/strong><\/p>\n<p>Azure AI developer, AI engineer, AI solution architect, Azure OpenAI consultant, ML engineer in Azure environment.<\/p>","inclus_dans_ce_cours_virtuel":"","inclus_dans_ce_cours_presentiel":"","inclus_dans_ce_cours_blended":"","inclus_dans_ce_cours_elearning":"","inclus_dans_ce_cours_surmesure":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.5 (Yoast SEO v27.5) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Develop AI apps and agents on Azure Training (AI-103) - ITTA<\/title>\n<meta name=\"description\" content=\"AI-103 Training: develop AI applications and agents in Azure AI Foundry, RAG, Azure OpenAI. 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