Microsoft Course: Develop AI agents on Azure
Azure AI Agent Development: From Single Bot to Collaborative Intelligence
- Architect intelligent agents using Azure AI Agent Service
- Implement Semantic Kernel for advanced agent logic
- Design multi-agent collaboration workflows
- Bridge AI models with business-specific operations
- Deploy scalable agent solutions in Azure environments
- Align with industry
- Build a base for specialized roles in AI development or cloud engineering
- Prepare for more advanced Microsoft certifications in AI
What you will learn
This 4-hour 28-minute technical learning path empowers developers to build next-generation AI agents using Azure's cutting-edge tools. Through 5 hands-on modules, engineers will master AI agent development using Azure AI Agent Service and Semantic Kernel Framework. From foundational concepts to multi-agent orchestration, the course covers custom tool integration, plugin development, and collaborative agent systems. Designed for cloud developers and AI practitioners, it combines theory with practical exercises for enterprise-grade AI solutions.
Microsoft's Develop AI agents on Azure course Outline
Learn the Develop AI agents on Azure
Ready to pioneer the future of autonomous AI systems? Microsoft's Develop AI Agents on Azure learning path equips engineers with battle-tested skills to build intelligent agents that automate complex workflows. Whether you're integrating custom APIs with Semantic Kernel or orchestrating collaborative agent networks, this 4.5-hour course offers hands-on labs and industry-proven patterns. Click to unlock Azure's full AI potential and earn certification credits – transform from coder to AI architect today!
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Course Structure Includes:
Module 1: Foundations (49 min)
- AI agent use cases & Azure development options
- Azure AI Agent Service exploration
Module 2: Core Development (55 min)
- Agent lifecycle management
- Service implementation best practices
Module 3: Customization (53 min)
- Tool integration frameworks
- API/plugin extension techniques
Module 4: Semantic Kernel (55 min)
- Agent logic programming
- Modular plugin architecture
Module 5: Multi-Agent Systems (56 min)
- Group chat orchestration
- Termination/selection strategies
Training Options
Self Paced Learning
- Lifelong access to high-quality content
- Curated by industry experts
- Customized learning progress
- 24/7 learner assistance and support
- Follow the latest technology trends
Exam Dump
- 100% Real Exam Practice Tests
- 100% Verified Exam Questions & Answers
- 100% Guarantee Passing Rate
- Average 7 Days to Practice & Pass
Description
Master AI agent development using Azure AI Agent Service and Semantic Kernel. Learn to build, customize, and orchestrate intelligent agents through hands-on labs and multi-agent system design.
Pre-requisites
Familiar with fundamental AI concepts and services in Azure.
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Benefits of AWS Certified AI Practitioner Certification
Microsoft Certified: Azure AI Fundamentals (AI-900) is an entry-level certification designed to validate foundational knowledge of AI and machine learning concepts, including computer vision, natural language processing (NLP), generative AI, and responsible AI principles. Ideal for both technical and non-technical professionals, it requires no prior coding experience and offers free, flexible learning resources via Microsoft Learn. The certification enhances career prospects in high-demand roles like AI Engineer or Data Scientist, with potential salary increases up to 20%, while serving as a gateway to advanced Azure certifications (e.g., AI-102). Cost-effective and time-efficient (preparation in 10–30 hours), the exam focuses on real-world applications using Azure Cognitive Services, OpenAI APIs, and Azure Machine Learning. With permanent validity and global recognition across 90+ countries, it equips professionals to drive AI innovation in industries such as healthcare and finance. Start your AI journey with Microsoft Learn today!
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SPOTO's study resources provide comprehensive coverage of the exam syllabus, aligning with key topics like ML problem framing, data processing, model optimization, and pipeline automation. The materials include structured learning paths, practice exams, and real-world case studies that mirror the certification's focus on designing, implementing, and deploying machine learning solutions with Microsoft services and ML workflows. By leveraging SPOTO's targeted content, candidates can efficiently bridge knowledge gaps, reinforce practical skills, and gain familiarity with the exam format. This focused preparation increases confidence and readiness, particularly for complex tasks such as deploying CI/CD pipelines or optimizing model performance—areas emphasized in the certification. Combined with hands-on experience, SPOTO's resources offer a strategic advantage for achieving certification success.
Online Learning Community
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