Microsoft GH-600 Exam Details & Actual Exam Questions

Exam Code/Number: GH-600
Exam Name/Title: Developing in Agentic AI Systems
Certification Provider: Microsoft
Corresponding Certification: GitHub Administrator

Exam Questions: 111
Updated On: Sep,20 2026
Certification Level: Associate

Microsoft Developing in Agentic AI Systems Exam Questions

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Microsoft GH-600 Exam Overview:

Certification Vendor:	Microsoft
Exam Name:	Developing in Agentic AI Systems
Exam Number:	GH-600
Exam Format:	Scenario-based, Multiple select, Multiple choice, Performance-based/lab tasks
Real Exam Qty:	40–60
Passing Score:	700
Certificate Validity Period:	2 years
Related Certifications:	Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure Developer Associate
Exam Price:	USD 100
Available Languages:	English
Exam Duration:	120–150
Recommended Training:	Semantic Kernel Documentation Azure AI Foundry Documentation GH-600 Learning Paths on Microsoft Learn
Exam Registration:	Pearson VUE Registration Microsoft GH-600 Exam Registration
Sample Questions:	Microsoft GH-600 Sample Questions
Exam Way:	Online proctored or Pearson VUE test center
Pre Condition:	Recommended: AZ-204 (Azure Developer Associate) or AI-102 (Azure AI Engineer Associate); proficiency in Python or C# and Azure development experience
Official Syllabus URL:	https://learn.microsoft.com/en-us/certifications/exams/gh-600

Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Test, deploy, and monitor agentic AI systems	20%	- Validate agent performance and safety 1. Evaluate quality metrics and iterate 2. Test reasoning accuracy and consistency 3. Apply guardrails and content safety - Deploy and monitor agents at scale 1. Optimize cost, latency, and throughput 2. Deploy to Azure AI and cloud environments 3. Implement logging, telemetry, and observability
Topic 2: Implement agents and multi-agent systems	30%	- Orchestrate multi-agent collaboration 1. Implement workflows and coordination strategies 2. Manage agent handoffs and task distribution 3. Define communication protocols between agents - Build agents with Azure AI tools and frameworks 1. Implement agent logic and reasoning 2. Develop using Semantic Kernel and Azure AI Foundry 3. Integrate models and prompts
Topic 3: Design agentic AI solutions	25%	- Define requirements for agentic systems 1. Identify use cases and scenarios 2. Plan for responsible AI and governance 3. Define functional and non-functional requirements - Design agent architecture 1. Plan tool integration and orchestration 2. Design memory and state management 3. Select agent patterns and topologies
Topic 4: Integrate tools, data, and services	25%	- Incorporate external tools and APIs 1. Handle authentication and error resilience 2. Design and register tool definitions 3. Implement function calling and service integration - Connect data sources and knowledge bases 1. Implement retrieval-augmented generation (RAG) 2. Ensure data security and access control 3. Integrate vector databases and search