Free Coupon Course for GitHub Copilot GH-300 Certification Exam [100% OFF]

You can find the discounted coupon code for this course at the end of this article

This course contains the use of artificial intelligence.

Additional Material

• Study Material [Download eBook in PDF}: Please download the PDF book (230 pages, study guide) as a companion resource for your certification exam preparation. The download link is provided in the Resources section of Practice Paper 1, Question 1. It is must you go through this book.

• Practice Paper: Include 2 Practice Paper, which cover entire syllabus with 120 practice Questions and Answers with detailed explanation.

Note: GitHub® and GitHub Copilot are registered trademarks of GitHub, Inc. This course material is not affiliated with or endorsed by GitHub, Inc.

Pass the GitHub Copilot Certification (GH-300) with a laser-focused, exam-ready program designed for real developers and teams. This course gives you everything you need to master the GH-300 blueprint—Responsible AI, Copilot plans and features, how Copilot works and handles data, prompt crafting/engineering, developer productivity use cases, testing, privacy fundamentals, and context exclusions—so you can walk into the exam confident and walk out certified. You’ll practice with official-style questions, hands-on prompt labs, and step-by-step workflows in VS Code or JetBrains, learning exactly how to use Copilot Chat, inline suggestions, and the CLI to accelerate day-to-day coding while staying compliant with enterprise policies.

Why this course stands out for GH-300:
• 100% certification preparation: domain-by-domain coverage mapped to the stated exam weighting.
• Practice-first design: exam-style questions with detailed explanations and rationales.
• Real workflows: prompt-to-PR scenarios, code review summaries, and test generation in modern stacks.
• Enterprise readiness: org policies, audit logs, content exclusions, duplication detection, and privacy settings explained with clear, reproducible steps.
• Responsible AI throughout: limitations, bias, secure coding, data handling, and validation strategies woven into every module.

What you’ll master (aligned to GH-300 domains):
• Responsible AI (7%): risks, limitations, validation, fairness, privacy, and secure-by-design practices you’ll be tested on.
• Plans & features (31%): Copilot Individual vs Business vs Enterprise, billing & data exclusions, Copilot Chat in IDE and on GitHub, multiple suggestion modes, exception handling, CLI, org-wide policy management, and audit log queries.
• How Copilot works & handles data (15%): context gathering, prompt construction, proxy filters, model response lifecycle, post-processing, matching code detection, and data flows for code completion vs Chat.
• Prompt crafting & engineering (9%): zero-shot vs few-shot, structuring prompts, chat history usage, context boundaries, and durable best practices.
• Developer use cases (14%): refactoring, debugging, documentation, sample data, legacy modernization, productivity metrics, and SDLC acceleration with measurable ROI.
• Testing with Copilot (9%): generating unit/integration tests, identifying edge cases, strengthening assertions, and editor configuration for higher-quality suggestions.
• Privacy & context exclusions (15%): repository/org exclusions, scope/limits, ownership of outputs, duplication detector, contractual protections, security checks, and troubleshooting.

Hands-on, practical learning:
• IDE setup quick start for VS Code/JetBrains/Neovim with Copilot Chat and inline assistance.
• Prompt labs: translate requirements into precise prompts; compare zero-shot vs few-shot; iterate for higher-quality completions.
• Testing drills: generate test suites, cover edge cases, and refine assertions to improve reliability.
• Enterprise controls: enable/disable duplication detection, configure content exclusions, and explore audit events to meet compliance.
• Troubleshooting guide: resolve “no suggestions,” fix sub-optimal context, and trigger Copilot effectively across editors.

Who this is for:
• Software developers, QA/test automation engineers, DevOps/SRE, data engineers, solution architects, tech leads, and engineering managers evaluating Copilot for teams.
• GitHub admins/program managers responsible for Business/Enterprise rollout, policy controls, and auditability.
• Anyone targeting GH-300 and wanting a clear, structured path from fundamentals to exam-ready proficiency.

What’s included:
• Domain-mapped lessons that mirror the GH-300 outline.
• Exam-style practice with full explanations and references for every answer.
• Downloadable checklists and cheat sheets: prompt engineering, privacy & exclusions, enterprise setup, and troubleshooting.
• Realistic scenarios that translate directly to daily work—prompt-to-PR, code review summaries, documentation generation, and metric tracking for Copilot impact.

Outcomes you can prove:
• Confidently compare Copilot plans and deploy the right SKU with the right policy controls.
• Explain and diagram how Copilot gathers context and produces responses—exactly what GH-300 tests.
• Apply prompt engineering to boost suggestion quality, reduce retries, and ship faster with fewer defects.
• Generate robust tests, catch edge cases early, and improve code health with Copilot-assisted assertions.
• Enforce privacy safeguards, content exclusions, and duplication detection to protect IP and reduce risk.
• Use productivity metrics to quantify Copilot ROI and communicate value to stakeholders.

Prerequisites:
No mandatory prerequisites. A GitHub account, an IDE (VS Code or JetBrains), and comfort with one programming language (Python, JavaScript/TypeScript, Java, C#, or Go) will help you get the most from the course.

If your goal is to pass GH-300 on the first attempt and adopt GitHub Copilot responsibly and effectively, this exam-ready course gives you the structure, practice, and confidence to succeed. Enroll now and turn AI-assisted development into a measurable advantage—on the exam and on the job.