GH-600 Course: Developing in Agentic AI Systems | GitHub and Agentic AI
The GH-600 course: Developing in Agentic AI Systems is an official Microsoft and GitHub training program aimed at professionals who wish to design, deploy, and manage agent-based artificial intelligence systems within modern development environments. The training focuses on using GitHub as the reference platform for coordinating, monitoring, and governing AI agents that actively participate in the software development lifecycle.
Agentic AI technology enables the creation of autonomous agents capable of planning, reasoning, using tools, interacting with execution environments, and collaborating with other agents to solve complex tasks. Integrated with GitHub, GitHub Copilot, MCP (Model Context Protocol), and DevOps flows, this technology helps accelerate development, improve team productivity, and automate software engineering processes.
In enterprise environments, Agentic AI systems are used to automate development tasks, code review, quality analysis, workflow execution, and the coordination of complex processes within the SDLC. The course provides practical insights into designing secure, reliable, and governed agent architectures for use in production environments.
Furthermore, this course is officially recognized by Microsoft, prepares for the GitHub Certified: Agentic AI Developer certification, and is eligible for FUNDAE funding for companies.
Course Overview
The GH-600: Developing in Agentic AI Systems course provides the necessary knowledge to design, implement, and manage agent-based artificial intelligence systems within modern development environments using GitHub as the control and monitoring platform.
During the training, participants will learn how to integrate AI agents into the software development lifecycle (SDLC), define agent architectures, configure tools and execution environments, manage memory and state, coordinate multiple agents, and apply monitoring and governance mechanisms to ensure reliable and secure results.
The course also covers key aspects related to GitHub Copilot, MCP Servers, observability, results evaluation, autonomous behavior control, and protection through guardrails. The practical approach allows for understanding how to deploy AI agents in real production environments while maintaining the quality, security, and control levels required by modern organizations.
What is the GH-600 Microsoft certification useful for in a professional setting?
The GH-600: Developing in Agentic AI Systems certification validates advanced skills in designing, deploying, monitoring, and governing agent-based artificial intelligence systems within modern development environments. It is aimed at professionals working with GitHub, GitHub Copilot, and Agentic AI architectures to automate complex processes in the software development lifecycle.
In the job market, this certification is especially relevant for profiles such as AI Engineer, Developer, DevOps Engineer, Solution Architect, Platform Engineer, and professionals responsible for integrating artificial intelligence into development processes. Organizations are increasingly seeking specialists capable of coordinating autonomous agents, monitoring their behavior, implementing control mechanisms, and ensuring secure and reliable results in production environments.
Obtaining the GH-600 certification improves employability and facilitates specialization in one of the most innovative areas of artificial intelligence applied to software development. It also allows participation in projects where intelligent agents collaborate with technical teams to accelerate software delivery, improve productivity, and optimize engineering processes.
Professional applications of GitHub and Agentic AI
GitHub and Agentic AI represent a new generation of technologies aimed at intelligent automation of software development. Through agents capable of planning, reasoning, executing tasks, and using tools autonomously, organizations can accelerate development processes and improve the productivity of their technical teams.
In enterprise environments, Agentic AI solutions are used to automate programming tasks, manage code reviews, coordinate DevOps flows, execute quality analysis processes, generate technical documentation, and collaborate with developers throughout the software lifecycle. GitHub acts as a control and monitoring platform, enabling the implementation of governance, observability, and security mechanisms to ensure reliable results.
The GH-600 course allows these technologies to be applied in real-world scenarios through the design and management of intelligent agent-based systems. Participants will learn to integrate GitHub Copilot, MCP Servers, multi-agent architectures, and control mechanisms to develop secure, scalable, and enterprise-ready artificial intelligence solutions.
What official Microsoft courses and certifications at Nanfor include
The training includes Microsoft Learn material, expert tutor presentations, authorized labs, specialized tutorials, and certification preparation.
Nanfor combines official Microsoft content with expert accompaniment, enabling training focused on practical application in real business environments.
Learn about all components
Advantages of GH-600 Training
Training in GH-600: Developing in Agentic AI Systems allows for the acquisition of advanced skills to design, deploy, and govern agent-based artificial intelligence systems within modern development environments using GitHub as the control platform.
- Learn to integrate AI agents into the software development lifecycle (SDLC).
- Design secure, scalable, and production-ready Agentic AI architectures.
- Work with GitHub Copilot, MCP Servers, and advanced automation tools.
- Manage memory, state, and execution of intelligent agents.
- Implement monitoring, observability, and autonomous behavior control mechanisms.
- Coordinate multi-agent systems to solve complex development processes.
- Apply governance, security, and responsibility practices in AI systems.
- Specialize in one of the fastest-growing areas within AI-based software engineering.
Additionally, this training provides practical knowledge on how to combine artificial intelligence, automation, and DevOps to accelerate development processes and improve the productivity of engineering teams.
Prerequisites
To get the most out of the GH-600 course, prior experience in software development, DevOps processes, and GitHub-based workflows is recommended.
Knowledge of the following is also advisable:
- GitHub and GitHub Copilot.
- Software Development Lifecycle (SDLC).
- Git, repositories, branches, and pull requests.
- Basic concepts of artificial intelligence and agents.
- Quality practices, code review, and security.
- General concepts of CI/CD.
The course is primarily aimed at developers, DevOps Engineers, AI Engineers, solution architects, and professionals working on the construction and operation of intelligent agent-based systems.
Preparation for Microsoft GH-600 Certification
This GH-600: Developing in Agentic AI Systems course prepares for the official GitHub Certified: Agentic AI Developer certification, providing the knowledge needed to design, implement, monitor, and govern Agentic AI systems using GitHub, GitHub Copilot, and advanced intelligent agent-based architectures.
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Course Duration:
70 hours
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Classroom Access:
2 months
General Course Information
Who is the Microsoft GH-600 course for?
The GH-600: Developing in Agentic AI Systems course is aimed at technical professionals who want to design, deploy, monitor, and govern agent-based artificial intelligence systems within modern software development environments.
It is particularly suitable for profiles such as AI Engineer, Developer, DevOps Engineer, Solution Architect, Platform Engineer, and professionals working with GitHub, GitHub Copilot, advanced automation, and intelligent agent-based architectures.
It is also aimed at development platform managers, software engineering teams, and artificial intelligence specialists who need to integrate, coordinate, and control autonomous agents within productive workflows, while maintaining adequate levels of security, quality, and governance.
GH-600 Course Objectives and What You Will Learn
Upon completion of the GH-600 course, you will be able to design, implement, and administer agent-based artificial intelligence systems within the software development lifecycle, using GitHub as a central platform for monitoring and controlling these systems.
- Understand the fundamentals of Agentic AI.
- Design agent architectures integrated into modern SDLC processes.
- Configure tools, permissions, and execution environments for intelligent agents.
- Work with GitHub Copilot, MCP Servers, and advanced automation mechanisms.
- Manage memory, state, and context of AI agents.
- Monitor autonomous behavior using controls and observability mechanisms.
- Evaluate and optimize results generated by Agentic AI systems.
- Coordinate multi-agent architectures to solve complex development tasks.
- Implement guardrails, security policies, and governance mechanisms.
- Prepare for the GitHub Certified: Agentic AI Developer certification.
Elements of the GH-600 Microsoft Learn collection
The official Microsoft Learn collection associated with the GH-600 course includes the following learning paths:
- Developing in Agentic AI Systems – Part 1 of 2
- Developing in Agentic AI Systems – Part 2 of 2
These learning paths allow participants to acquire the knowledge necessary to design Agentic AI architectures, integrate agents within the software development lifecycle, manage execution environments, coordinate multi-agent systems, and apply security and governance practices using GitHub as the control platform.
GH-600 Course Content – Official Program
Our differentiating factor: Practical Labs
One of the differentiating elements of the GH-600: Developing in Agentic AI Systems course is its practical approach focused on real-world scenarios of developing, deploying, and governing intelligent agents. Through guided labs, participants learn to work with GitHub, GitHub Copilot, Agentic AI architectures, and multi-agent systems used in modern software engineering environments.
Practical exercises enable understanding of how to integrate agents into the software development lifecycle (SDLC), monitor their behavior, manage tools and execution environments, and apply the control and governance mechanisms necessary for production environments.
| Nanfor Labs |
Developed technical skills |
Practical learning outcome |
| Lab 1: Fundamentals of Agentic AI in GitHub |
Understanding Agentic AI architectures, intelligent agent operation, integration with GitHub, and use within the software development cycle |
Ability to identify scenarios where agents can provide automation and productivity within development teams |
| Lab 2: Designing agent architectures |
Defining agent responsibilities, separating planning, reasoning, and execution tasks, designing interaction flows |
Building reliable, scalable, and enterprise-ready Agentic AI architectures |
| Lab 3: Integrating agents into the SDLC |
Incorporating intelligent agents into development flows, integrating with repositories, code reviews, and DevOps processes |
Ability to automate tasks within the software lifecycle using AI agents |
| Lab 4: Configuring tools and MCP Servers |
Configuring external tools, Model Context Protocol (MCP), permissions, and interaction capabilities with services |
Creating secure environments where agents can use controlled tools and resources |
| Lab 5: Memory, state, and context management |
Managing agent memory, context persistence, and state control during complex executions |
Implementing agents capable of maintaining consistency and continuity in long-running processes |
| Lab 6: Secure execution of autonomous agents |
Execution control, setting operational limits, managing permissions, and behavior policies |
Ability to deploy agents with protective mechanisms that reduce operational risks |
| Lab 7: Agent monitoring and observability |
Monitoring activities, analyzing events, generating metrics, and tracking autonomous behavior |
Full visibility into agent operation and ability to intervene when necessary |
| Lab 8: Evaluation and optimization of results |
Validating responses, quality analysis, performance evaluation, and continuous improvement of agents |
Ability to increase the accuracy, efficiency, and reliability of Agentic AI systems |
| Lab 9: Multi-agent system coordination |
Orchestrating multiple specialized agents, coordinating tasks, and distributing responsibilities |
Implementing complex solutions where multiple agents collaborate to achieve shared goals |
| Lab 10: Governance, guardrails, and responsibility |
Applying security policies, approval mechanisms, auditing, and governance of intelligent agents |
Ability to deploy Agentic AI solutions aligned with enterprise security and compliance requirements |
Thanks to these labs, participants gain practical experience in building and operating Agentic AI systems, acquiring knowledge directly applicable to real projects in development, automation, and governance of intelligent agents on GitHub.
Course Language
- Course: English / Spanish
- Labs: English / Spanish
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Nanfor, official Microsoft ICT training center
Nanfor is a customized IT training center, specializing in technology training for professionals and companies, and is officially accredited by Microsoft as:
- Microsoft Solutions Partner – Training Services
- Microsoft Cloud Partner
These accreditations certify that Nanfor meets Microsoft's standards for delivering technical courses, using Microsoft content and Microsoft Certified Trainers (MCTs), ensuring quality, continuous updates, and alignment with certifications.
Frequently Asked Questions about the GH-600 Course
What is the GH-600 GitHub and Agentic AI course?
The GH-600 GitHub and Agentic AI course is an official Microsoft and GitHub training focused on the design, deployment, and governance of agent-based artificial intelligence systems within modern software development environments.
What is the GH-600 GitHub and Agentic AI certification for?
The GH-600 certification validates skills in creating, monitoring, and managing Agentic AI systems, helping organizations integrate intelligent agents into software development, automation, and operation processes.
Is the GH-600 GitHub and Agentic AI course official from Microsoft?
Yes. The GH-600 course is an official Microsoft and GitHub training based on Microsoft Learn and aligned with the GitHub Certified: Agentic AI Developer certification.
How does the GH-600 GitHub and Agentic AI course differ from other Microsoft AI-related certifications?
The GH-600 course specializes in Agentic AI systems, addressing agent architectures, multi-agent coordination, observability, MCP Servers, autonomous monitoring, and governance within GitHub and DevOps environments, areas not typically covered in more traditional AI certifications.
Is the GH-600 GitHub and Agentic AI course eligible for FUNDAE funding?
Yes. The GH-600 GitHub and Agentic AI course is eligible for FUNDAE funding for companies, allowing them to recover all or part of the investment made in training according to available credits.
What is the duration of the GH-600 GitHub and Agentic AI course?
The GH-600 course has an official duration of 1 day of Microsoft instructor-led training, complemented by official materials, practical labs, and additional learning resources.
Is the GH-600 GitHub and Agentic AI course included in Nanfor's LaaS?
Yes. The GH-600 GitHub and Agentic AI course can be part of Nanfor's LaaS programs, facilitating continuous access to specialized training in artificial intelligence, automation, and modern software development.
What technical level does the GH-600 GitHub and Agentic AI course require?
The GH-600 course is aimed at an intermediate level. Prior experience in GitHub, GitHub Copilot, SDLC, DevOps, software development, and basic concepts of artificial intelligence and agents is recommended.
What career opportunities does the GH-600 GitHub and Agentic AI course offer?
The GH-600 course allows for the development of profiles such as AI Engineer, Developer, DevOps Engineer, Platform Engineer, Solution Architect, or specialist in intelligent agent-based automation within modern business environments.
