GH-600 GitHub Certified Agentic AI Developer Video Course

What you'll learn

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Map every GH-600 domain to the concrete decision an agent forces during real work
Choose agent work by shape: bounded input, checkable output, a done a machine can check
Configure tools, MCP servers, allow lists, and CI lanes with least privilege
Diagnose agent failures from logs, plans, and traces, then fix the layer that failed
Coordinate several agents with orchestration patterns, isolation lanes, and collision detection
Attach autonomy to action classes and guard irreversible actions with explicit authorization
Requirements

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Working knowledge of Git and GitHub: branches, pull requests, reviews
No agent experience required; every concept is taught from its failure case first
Description

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The video course for GH-600. Most GH-600 prep is a stack of practice questions with no teaching behind it. This course teaches the exam: all six domains of the GitHub Certified Agentic AI Developer certification, each taught through a real failure an agent caused, then worked as an exam question with the wrong options killed one by one.
What makes it different
- Six domains as one story: one agent, one repository, one workday. What runs before the agent acts, the tools in its hands, what it remembers, the reckoning when its work is judged, the colleagues it coordinates with, and the rules of the house.
- Two elimination rules pulled from the study guide's own wording: a prompt is not a permission, and size the gate to the risk. Name the risk first and four plausible options collapse to two.
- A worked question inside every lesson, in the exam's own scenario style.
- Concept-first, so it stays current: no UI walkthroughs that go stale, no version trivia.
Full coverage at the weights the study guide publishes
- Domain 1, agent architecture and SDLC integration (15 to 20 percent): lessons 2 and 3
- Domain 2, tool use and environment interaction (20 to 25 percent, the largest domain): lessons 4, 5, and 6
- Domain 3, memory, state, and execution management (10 to 15 percent): lesson 7
- Domain 4, evaluation, error analysis, and tuning (15 to 20 percent): lessons 8 and 9
- Domain 5, multi-agent coordination (15 to 20 percent): lessons 10 and 11
- Domain 6, guardrails and accountability (10 to 15 percent): lesson 12
The exam: 120 minutes, 700 of 1000 to pass, renewed yearly through a free online assessment.
Start with the free preview lesson: the whole exam decoded as one agent's workday.
AI disclosure: AI tools were used in producing this course. The curriculum, the exam facts, and every lesson were verified by the instructor against the current official exam guide.
Who this course is for

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Developers preparing for the GH-600 GitHub Certified Agentic AI Developer exam
Engineers bringing coding agents into team workflows who need the governance patterns the exam tests
Homepage

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