Develop AI solutions in Azure
Build AI-infused applications in Azure and gain the skills to develop generative AI apps, AI agents and intelligent solutions using Azure AI Foundry and other Azure AI services. This course is ideal for software developers who want to create advanced AI solutions and integrate AI capabilities into their applications.
R11,900.00 Excl. VAT
Product Details
AI-102: Develop AI solutions in Azure is designed for software developers looking to build AI-infused applications using Azure AI Foundry and other Azure AI services. The course covers developing generative AI applications, building AI agents, and creating solutions that implement computer vision and information extraction
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Download Outline ➤ MS-AI102T00 – Develop AI Solutions in Azure
Watch an informative video ➤ Introducing new deployment and cost management solutions for Azure OpenAI Service
Associated Certification & Exam
This course will prepare delegates to write the AI-102: Designing and Implementing an Azure AI Solution exam
COURSE CONTENT
Module 1: Develop generative AI apps in Azure
Generative Artificial Intelligence (AI) is becoming more accessible through comprehensive development platforms like Azure AI Foundry. Learn how to build generative AI applications that use language models to chat with your users.
Module 1.1: Plan and prepare to develop AI solutions on AzureMicrosoft Azure offers multiple services that enable developers to build AI-powered solutions. Proper planning and preparation involve identifying the services you will use and creating an optimal working environment for your development team. |
Module 1.2: Choose and deploy models from the model catalogue in Azure AI Foundry portalChoose from the various language models available through the Azure AI Foundry model catalogue. Understand how to select, deploy and test a model and improve its performance. |
Module 1.3: Develop an AI app with the Azure AI Foundry SDKUse the Azure AI Foundry SDK to develop AI applications with Azure AI Foundry projects. |
Module 1.4: Get started with prompt flow to develop language model apps in Azure AI FoundryLearn how to use prompt flow to develop applications that leverage language models in Azure AI Foundry. |
Module 1.5: Develop a RAG-based solution with your own data using Azure AI FoundryRetrieval Augmented Generation (RAG) is a common pattern used in generative AI to ground prompts with your data. Azure AI Foundry enables adding data, creating indexes and integrating them with generative AI models to build RAG-based solutions. |
Module 1.6: Fine-tune a language model with Azure AI FoundryTrain a base language model on a chat-completion task. Azure AI Foundry provides open-source models that can be fine-tuned for your specific behavioural needs. |
Module 1.7: Implement a responsible generative AI solution in Azure AI FoundryGenerative AI enables creative solutions but must be implemented responsibly to minimise harmful content generation and ensure safe usage. |
Module 1.8: Evaluate generative AI performance in Azure AI Foundry portalEvaluating copilots is essential to ensure that generative AI applications meet user needs and provide accurate responses. Learn how to assess and optimise performance using Azure AI Studio tools. |
Module 2: Develop AI agents on Azure
AI agents are becoming a key component of modern generative AI solutions. This learning path helps you understand when to use agents and how to build them using Azure AI Foundry Agent Service and the Semantic Kernel Agent Framework.
Module 2.1: Get started with AI agent development on AzureAI agents represent the next generation of intelligent applications. Learn how they can be developed and used on Microsoft Azure. |
Module 2.2: Develop an AI agent with Azure AI Foundry Agent ServiceThis module provides engineers with the skills to begin building agents with Azure AI Foundry Agent Service. |
Module 2.3: Integrate custom tools into your agentBuilt-in tools are useful but may not meet all needs. Learn how to extend your agent by integrating custom tools. |
Module 2.4: Develop a multi-agent solution with Azure AI Foundry Agent ServiceBreak down complex tasks through intelligent collaboration. Learn how to design multi-agent solutions using connected agents. |
Module 2.5: Integrate MCP Tools with Azure AI AgentsEnable dynamic tool access for Azure AI agents. Learn how to connect MCP-hosted tools and integrate them into agent workflows. |
Module 2.6: Develop an AI agent with Microsoft Agent FrameworkLearn how to build Azure AI Foundry Agent Service agents using the Microsoft Agent Framework. |
Module 2.7: Orchestrate a multi-agent solution using Microsoft Agent FrameworkLearn how to use the Microsoft Agent Framework SDK to develop AI agents that collaborate in multi-agent solutions. |
Module 2.8: Discover Azure AI Agents with A2ALearn how to implement the A2A protocol to enable agent discovery, direct communication and coordinated task execution across remote agents. |
Module 3: Develop natural language solutions in Azure
Natural language solutions use language models to interpret and respond to written or spoken language. Azure AI services enable you to build intelligent language-powered applications.
Module 3.1: Analyse text with Azure AI LanguageThe Azure AI Language service enables you to create intelligent apps and services that extract semantic information from text. |
Module 3.2: Create question answering solutions with Azure AI LanguageThe question answering capability enables natural language interactions where users ask questions and receive accurate answers. |
Module 3.3: Build a conversational language understanding modelUse Azure AI Language CLU to train a model that extracts intents and entities from natural language. |
Module 3.4: Create a custom text classification solutionLearn how to build a custom text classification solution using Azure AI Language service. |
Module 3.5: Custom named entity recognitionBuild a custom entity recognition solution to extract entities from unstructured documents. |
Module 3.6: Translate text with Azure Translator serviceThe Translator service enables you to create intelligent applications that translate text between languages. |
Module 3.7: Create speech-enabled apps with Azure AI servicesUse Azure AI Speech APIs for speech recognition and speech synthesis to build speech-enabled apps. |
Module 3.8: Translate speech with the Azure AI Speech serviceLearn how to transcribe speech in one language and return translations in another using the Azure AI Speech service. |
Module 3.9: Develop an audio-enabled generative AI applicationLearn how to build audio-enabled chat applications that listen and respond to voice inputs using generative AI models. |
Module 4: Develop computer vision solutions in Azure
Computer vision enables apps to interpret and understand visual content. Azure AI provides multiple tools for common computer vision scenarios.
Module 4.1: Analyse imagesUse the Azure AI Vision service to analyse images and extract insights using pre-trained models. |
Module 4.2: Read text in imagesLearn how to use the Image Analysis API for OCR to extract text from images. |
Module 4.3: Detect, analyse and recognise facesLearn how to detect human faces, analyse facial features and emotions and recognise individuals. |
Module 4.4: Classify imagesUse Azure AI Custom Vision to train a model that classifies images based on your categories. |
Module 4.5: Detect objects in imagesUse Azure AI Custom Vision to train object detection models. |
Module 4.6: Analyse videoUse Azure Video Indexer to extract insights from video such as text, labels, face identification and scene segmentation. |
Module 4.7: Develop a vision-enabled generative AI applicationUse multimodal generative models to build chat applications that understand and respond to images. |
Module 4.8: Generate images with AIUse Azure AI Foundry image generation models to create original images from natural language prompts. |
Module 5: Develop AI information extraction solutions in Azure
Use AI to extract information from content to support Data capture, automation, meeting summarisation, Digital asset management and knowledge mining.
Module 5.1: Create a multimodal analysis solution with Azure AI Content UnderstandingUse Azure AI Content Understanding for multimodal content analysis and information extraction. |
Module 5.2: Create an Azure AI Content Understanding client applicationUse the Azure AI Content Understanding REST API for multimodal content analysis and information extraction. |
Module 5.3: Use prebuilt Document Intelligence modelsLearn what data you can analyse by choosing prebuilt Forms Analyzer models and how to deploy them in a Document Intelligence solution. |
Module 5.4: Extract data from forms with Azure Document IntelligenceLearn how to extract key-value pairs and table data from forms at scale using Azure Document Intelligence. |
Module 5.5: Create a knowledge mining solution with Azure AI SearchUnlock insights in your data with Azure AI Search. Learn how to extract and enrich data to make it searchable for deeper analysis. |
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