Microsoft Generative and Agentic AI Basics

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Build practical generative and agentic AI development skills using Microsoft Azure and Azure AI Foundry. This specialization guides you through the modern AI application lifecycle, from understanding Large Language Models (LLMs) to building intelligent AI agents and automated workflows for real-world use cases. You'll begin with the foundations of generative AI, prompt engineering, and LLM interactions in Azure. As you progress, you'll build Retrieval-Augmented Generation (RAG) pipelines, fine-tune models for domain-specific applications, and deploy scalable AI-powered solutions. The specialization also introduces AI agent development with Azure AI Foundry, where you'll design, configure, and test intelligent agents for customer and healthcare scenarios while integrating language, translation, speech, search, and vision capabilities. Through hands-on projects, you'll move from visual development tools to programmatic orchestration using Azure Functions, APIs, and Logic Apps, and learn testing strategies, deployment workflows, and enterprise AI automation techniques. By the end, you'll be able to build context-aware AI systems, orchestrate intelligent workflows, integrate external tools and APIs, and develop production-ready generative AI applications within the Microsoft ecosystem. This specialization is designed for developers and technical professionals who want to expand their AI development skills using Microsoft Azure technologies.

Syllabus

Course 1: Getting started with generative AI in Azure
Course 2: Working with large language models using Azure
Course 3: AI agent fundamentals with Azure AI Foundry
Course 4: Building intelligent agent workflows

Courses

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Learn how to design, build, and evaluate intelligent AI agents using Microsoft Azure AI Foundry. This hands-on course introduces the foundations of AI agent development and guides you through creating practical agents that can respond to real-world scenarios using modern Azure AI services. You’ll begin by exploring how AI agents differ from traditional automation systems and how reactive, deliberative, and hybrid agents operate in different use cases. Using Azure AI Foundry, you’ll learn to configure models, deploy AI services, and create effective system prompts that improve agent behavior and response quality. As the course progresses, you’ll build a portfolio-ready hotel information agent capable of handling guest inquiries, managing conversations, and integrating knowledge sources. You’ll also enhance agent capabilities using Azure AI services including language understanding, search, translation, sentiment analysis, and multimodal AI tools. The course concludes with testing, deployment, and portfolio development strategies that help you understand how AI agents operate in production environments. By the end of this course, you’ll be able to build, evaluate, and deploy intelligent AI agents using Azure AI Foundry and related Azure AI services.
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Advance your AI development skills by building intelligent agent workflows and enterprise-ready AI systems using Microsoft Azure. This hands-on course focuses on creating context-aware AI agents, integrating multiple AI services, and orchestrating automated workflows for real-world healthcare scenarios. You’ll begin by exploring Azure AI services and learning how to design safe, reliable AI agents for sensitive environments. Using Azure AI Foundry, Azure Functions, and Logic Apps, you’ll develop healthcare-focused AI assistants that combine language understanding, search, translation, speech, and workflow automation capabilities. The course also introduces advanced conversation management techniques, contextual memory strategies, and Retrieval-Augmented Generation (RAG) integrations to improve agent intelligence and response quality. As you progress, you’ll move from UI-based development to programmatic orchestration, connecting agents with external APIs, custom tools, and enterprise workflows. You’ll also learn testing, deployment, and automation strategies used in production AI systems, including workflow approvals, error handling, and compliance-aware development practices. By the end of this course, you’ll be able to build sophisticated AI agent workflows that integrate Azure AI services, automation tools, and custom orchestration strategies for enterprise applications.
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Learn how to build, customize, and deploy generative AI applications using Large Language Models (LLMs) and Microsoft Azure. This hands-on course introduces the practical techniques developers use to improve AI application performance, reliability, and business relevance. You’ll begin by exploring how LLMs work, including their architecture, capabilities, and limitations. From there, you’ll apply prompt engineering strategies to improve model outputs and build more effective AI interactions. The course then introduces Retrieval-Augmented Generation (RAG) pipelines, teaching you how to connect LLMs with external data sources to deliver grounded, accurate responses. You’ll also learn how to customize models using fine-tuning techniques and evaluate when to use fine-tuning, RAG, or hybrid approaches for different business scenarios. In the final modules, you’ll build and deploy generative AI applications using Azure AI Foundry and Azure OpenAI services while learning deployment, monitoring, and cost management strategies. By the end of this course, you’ll have practical experience building AI-powered applications using modern Azure AI tools and workflows.
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Dive into the transformative world of generative AI with Microsoft Azure! This course is your hands-on introduction to building intelligent applications, taking you from core concepts to completing multiple hands-on projects. You will start by understanding the fundamentals of what makes generative AI unique and explore its evolution from traditional AI models to the generative approach. Next, you'll get acquainted with the Azure AI Foundry, Microsoft's powerful platform for AI development. Through practical labs and activities, you will learn to set up your environment, experiment with different AI models, and configure key parameters. The course culminates in you designing, building, and refining your own text generation application. Crucially, you will also learn to integrate essential ethical principles, ensuring your AI solutions are responsible and safe. By the end, you won't just understand generative AI; you'll have the practical skills to build with it.