GitHub Certified Agentic AI Developer (GH-600)
GitHub Certified Agentic AI Developer (GH-600)
GitHub Certified Agentic AI Developer (GH-600) Practice Exam
The GitHub Certified: Agentic AI Developer (GH-600) certification validates the knowledge and practical skills required to build, configure, orchestrate, evaluate, and govern AI agents within modern software development environments. As AI-powered development becomes increasingly integrated into enterprise workflows, organizations need professionals who can effectively leverage autonomous and semi-autonomous AI agents while maintaining security, compliance, quality, and operational efficiency.
Exam Prerequisites
Although there are no mandatory prerequisites, candidates are recommended to have:
- Experience using GitHub repositories and workflows
- Understanding of software development lifecycle practices
- Familiarity with AI-assisted coding tools
- Knowledge of DevOps concepts and automation
- Basic understanding of APIs and integrations
- Exposure to AI and machine learning concepts
- Awareness of security and governance practices
Who should take the exam?
This certification is designed for:
- Software Developers
- Application Developers
- AI Engineers
- DevOps Engineers
- Platform Engineers
- Solutions Architects
- Engineering Managers
- GitHub Copilot Users and Administrators
- Automation Engineers
- Technical Leads
- Security Professionals involved in AI governance
Course Outline
The GitHub Certified Agentic AI Developer (GH-600) Exam covers the following topics -
- Domain 1. Prepare Agent Architecture and SDLC Processes (15–20%)
- Domain 2. Implement tool use and environment interaction (20–25%)
- Domain 3. Manage memory, state, and execution (10–15%)
- Domain 4. Perform evaluation, error analysis, and tuning (15–20%)
- Domain 5. Orchestrate multi-agent coordination (15–20%)
- Domain 6. Implement guardrails and accountability (10–15%)
Knowledge Gained
Upon completing preparation for the GitHub Certified: Agentic AI Developer (GH-600) certification, learners will gain knowledge in:
- Agentic AI Fundamentals
- GitHub and AI Integration
- Tooling and Environment Management
- Agent Memory and Context Management
- Agent Evaluation and Optimization
- Multi-Agent Systems
- Governance, Security, and Compliance
- Enterprise AI Adoption
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