- Choosing the steps an agent should perform and avoiding common agent anti-patterns.
- Defining inputs, outputs and success criteria for agents.
- Keeping planning separate from execution, with structured plans that are validated before the agent acts.
- Setting the degree of autonomy, inspectable artifacts and human intervention that does not slow delivery.
GitHub Certification Training Course
GitHub Agentic AI Developer (GH-600) Certification Training Course
Run AI agents safely inside your software delivery process, with GitHub as the control plane, and get ready for the GitHub Agentic AI Developer (GH-600) exam with Accumentum’s live online training.
Course focus: Plan, configure, evaluate and govern AI agents inside GitHub workflows, from tools and MCP servers to memory, multi-agent orchestration and guardrails, and prepare for the GitHub Agentic AI Developer (GH-600) exam.
Course Overview
Operate, supervise and govern AI agents inside a real software delivery process.
AI agents can now open branches, write code and raise pull requests on their own. This course is for the engineers who run those agents in a real SDLC and have to keep them reliable and safe. We use GitHub as the system of record and control plane for everything the agents do.
The course follows the official GH-600 skills outline. You will plan agent work and keep planning separate from action, configure tools and MCP servers, scope agents to repositories and CI workflows, manage memory and state, evaluate and tune agent output, coordinate multiple agents, and set guardrails with human review where it counts.
By the end you will know how to give agents enough autonomy to be useful without losing control or traceability. You will also be ready to sit the GitHub Agentic AI Developer exam.
Course Objectives
Build agentic AI skills and GH-600 exam readiness.
01
Agent Architecture
Define what agents should do in the SDLC, with clear inputs, outputs, success criteria and structured plans.
02
Tools and MCP
Configure agent tools, permissions and MCP servers, and scope agents to repositories, branches and CI workflows.
03
Evaluation and Orchestration
Evaluate agent output, trace failures to root causes, and coordinate multiple agents without conflicts.
04
GH-600 Exam Readiness
Cover all six domains in the official GH-600 skills outline, including memory, state and guardrails.
Who Should Attend
- Software engineers who run coding agents such as GitHub Copilot inside their team’s SDLC.
- Platform and DevOps engineers who wire agents into CI workflows and need them to fail safely.
- Architects and security engineers who decide how much autonomy agents get and where humans step in.
- Application developers and product managers who work alongside agents and want to understand how they are governed.
Prerequisites
- There are no formal prerequisites for the GH-600 exam or for this course.
- GitHub recommends reviewing the related Microsoft Learn modules before the exam. We cover the same skills in class.
- You should have experience with the SDLC, GitHub workflows and controls, and code quality, security and review practices.
- Hands-on time with coding agents such as GitHub Copilot, MCP servers and agent customization like custom instructions, custom agents, tools and Copilot setup steps will help.
Pathway Map
The GitHub Agentic AI Developer course follows the six GH-600 skill domains.
Each module maps to an official exam domain and its published weight, from agent architecture to guardrails and accountability.
Course Content
- Identifying and configuring agent tools and tool permissions.
- Adding MCP servers, configuring the GitHub remote MCP server, MCP registries and MCP allow lists.
- Scoping agents to a repository or branch, invoking them in CI workflows and letting them create branches and pull requests.
- Error handling, retries, rollbacks, escalation paths and traceability for agent actions.
- Choosing between short-term, long-term and external memory and scoping it to the task.
- Rules for memory expiration, pruning and reset.
- Capturing progress and decisions as durable artifacts so agents can resume without repeating work.
- Detecting drift and preventing stale or conflicting context across tools and environments.
- Setting expected outcomes, constraints and evaluation signals for agent tasks.
- Generating evaluation signals with automated scanning tools.
- Finding failures in logs, plans, traces and workflow artifacts and classifying root causes.
- Tuning instructions, workflows, memory and tool access based on results.
- Applying an orchestration pattern and isolating agents for parallel work.
- Resolving overlapping changes, duplicated effort and contradictory output.
- Producing artifacts and decision records that support review, audit and post-hoc analysis.
- Recovering from failed or stalled runs and adding, updating or retiring agents without breaking workflows.
- Classifying agent actions by operational, security and compliance risk.
- Assigning autonomy levels that keep delivery fast and stay within Responsible AI standards.
- Blocking actions that break policy and scoping permissions to least privilege.
- Requiring explicit approval for irreversible changes while skipping approvals that do not reduce risk.
Course Features
Built for practical agentic AI training and GH-600 exam prep.
Interactive Learning
Participate in training sessions, discussions, and hands-on labs with experienced instructors.
Comprehensive Study Materials
Access extensive resources, including e-books, video lectures, and practice exams.
Practical Scenarios
Engage in real-world exercises and case studies to apply GitHub Agentic AI Developer concepts.
Certification Preparation
Receive guidance and tips to successfully pass the GitHub Agentic AI Developer exam.
Certification Exam
Prepare for the official GitHub Agentic AI Developer exam.
GH-600 Exam Readiness
Accumentum’s GitHub Agentic AI Developer course follows the official GH-600 skills outline and prepares you for every domain on the exam.
After the course you will be ready to take the official GitHub Agentic AI Developer (GH-600) exam. GitHub says it validates your ability to operate, supervise and govern autonomous AI agents within GitHub-driven SDLC workflows.
The exam is intermediate level and runs 120 minutes. You can take it at a Pearson VUE testing center or online. It is currently offered in English. A score of 700 or higher is required to pass.
The certification is valid for 2 years. GitHub is moving to Microsoft’s recertification process, which will let you keep your certification current without retaking the full exam.
Frequently Asked Questions
Answers to common questions about Accumentum’s GitHub Agentic AI Developer course, the GH-600 exam, eligibility, delivery and payment.
It shows you can deploy, operate, integrate and govern AI agents in production SDLC workflows, using GitHub as the control plane. The exam code is GH-600.
Engineers who run AI agents in their software delivery process. That includes platform and DevOps engineers, architects, application developers and security engineers who work with agents.
There are no formal prerequisites. You should know the SDLC and GitHub workflows, and have hands-on time with coding agents like GitHub Copilot and MCP servers. GitHub recommends reviewing the related Microsoft Learn modules first.
Six domains: agent architecture and SDLC processes (15 to 20%), tool use and environment interaction (20 to 25%), memory, state and execution (10 to 15%), evaluation, error analysis and tuning (15 to 20%), multi-agent coordination (15 to 20%), and guardrails and accountability (10 to 15%).
The exam runs 120 minutes. You can take it at a Pearson VUE testing center or online. It is currently offered in English.
You need a score of 700 or higher.
It is valid for 2 years. GitHub is moving to Microsoft’s recertification process, which will let you renew without retaking the full exam.
The course is delivered live online by an instructor, with hands-on practice in GitHub between sessions.
Yes. PathPay lets you pay for your training over time instead of all at once. You can enroll through PathPay from this page or contact us with any questions.
Enrollment
Enroll in the GitHub Agentic AI Developer (GH-600) Certification Training Course with Accumentum.
Enroll in the GitHub Agentic AI Developer (GH-600) Certification Training Course with Accumentum to learn how to run AI agents in your SDLC without losing control. You will cover every GH-600 domain, from agent planning, tools and MCP servers to memory, evaluation, multi-agent orchestration and guardrails.
When you finish, you will be ready to sit the GitHub Agentic AI Developer exam and bring agents into your delivery process with confidence. For upcoming class dates and to save your seat, use the registration page linked below.
Put AI agents to work safely with GitHub Agentic AI Developer training.
Prepare for the GitHub Agentic AI Developer (GH-600) exam and learn to run agents in your SDLC with the right tools, checks and guardrails.