Microsoft AI Agents: From Foundations to Applications

Microsoft via Coursera Professional Certificate

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Provider

Coursera Professional Certificate
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

8 weeks, 8 hours a week
Sessions

Self-Paced
Level

Intermediate

Found in

Overview

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This certificate is for developers with solid programming basics who want to transition into an AI Agent Developer role. You'll build a strong foundation using Azure AI Foundry and then progress to advanced, code-based development. The curriculum will prepare you for enterprise-level challenges, where you’ll build scalable, secure, and responsible multi-agent systems. You'll gain practical skills and create a portfolio of projects to showcase your expertise. Throughout the courses, you'll use the Microsoft Azure AI ecosystem to create intelligent solutions, gaining a competitive edge in a rapidly growing field. This certificate focuses on production-ready skills, providing a clear path from foundational concepts to advanced, deployable systems. You will build a hotel information agent, a medical information agent, and a multi-agent system, all while learning best practices for testing, deployment, and security. Upon completion, you’ll be able to: Design and implement multi-agent systems using the AutoGen framework. Develop production-ready agents with Python, Bot Framework, and Semantic Kernel. Apply enterprise security and Responsible AI principles for secure deployments. Create comprehensive portfolios showcasing your skills for career transition. Prerequisites: Basic: Background in programming basics (any language) and cloud computing concepts. Advanced: Comfort with Python fundamentals, including async programming and REST APIs, is recommended.

Syllabus

Course 1: AI agent fundamentals with Azure AI Foundry
Course 2: Building intelligent agent workflows
Course 3: Code and framework based agent development
Course 4: Building multi-agent systems

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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This course is designed to elevate skilled developers into multi-agent system architects. You'll learn to design and implement collaborative AI systems. The course focuses on building scalable, production-ready systems, ensuring responsible AI, and applying enterprise security and integration patterns. You'll complete a project where specialized agents work together to solve a complex business problem. By the end of this course, you will be able to: - Design and document sophisticated multi-agent architectures for enterprise applications. - Build and orchestrate multi-agent systems using the AutoGen framework. - Implement enterprise-grade security with Azure Entra ID and integrate with SharePoint. - Deploy and monitor multi-agent systems using Docker and understand Kubernetes requirements. - Apply Microsoft's responsible AI principles.
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This course is designed to transition experienced developers into AI agent specialists through intensive, hands-on coding. You'll build production-ready systems by using AI frameworks and integrating advanced language models. You'll benefit by learning to build secure, cost-optimized agents and connect them to the Microsoft 365 ecosystem. By the end of this course, you will be able to: - Integrate Azure OpenAI Service for complex reasoning and implement prompt chaining strategies. - Develop professional conversational bots using Python and the Bot Framework. - Simplify AI orchestration by creating reusable plugins and memory systems with Semantic Kernel. - Connect agents to the Microsoft 365 ecosystem using the Microsoft Graph API for data access and report generation. - Implement production-ready features, including error handling, security, and cost-optimization.