Training course · GitHub Copilot · Internal Tools & Automation

GitHub Copilot for Internal Tools and Automation

Use GitHub Copilot professionally: completions, chat, agent mode, the coding agent for issues and PRs, code review and enterprise policies.

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects GitHub Copilot with the everyday processes of Internal Tools & Automation. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

GitHub Copilot has grown from simple code completion into a broad AI platform that supports the entire development lifecycle. In the editor you work with inline suggestions, next edit suggestions and Copilot Chat; in agent mode Copilot handles tasks across multiple files and runs commands. On GitHub itself, the coding agent picks up assigned issues and delivers pull requests. In this two-day course you will learn how to use each of these building blocks deliberately and fit them cleanly into your existing development process.

Beyond hands-on editor work, the course covers control and quality. Custom instructions and prompt files give Copilot the project knowledge it needs, MCP adds further tools, and Copilot code review complements human reviewers. For those responsible for teams and organisations, we look at policies at organisation and enterprise level, content exclusions, model availability and usage reporting. Together, these lay the groundwork for a secure, transparent and genuinely effective Copilot rollout across the entire company.

Almost every company has a long backlog of small tools nobody gets round to building: admin interfaces for master data, scripts for recurring data reconciliation, Slack or Teams bots, report generators and glue between SaaS systems. With AI coding assistants and agents, internal tools like these can be built in hours rather than weeks. Developers, ops and platform teams therefore shift their focus from writing code to clear requirements, secure access and reliable operation. Internal tools in particular often hold far-reaching rights over production data and quickly become business-critical. In this course you learn to build internal tools and automations rapidly with AI, implement authentication and permissions correctly from the start and design solutions that stay documented, tested and maintainable.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Software developers maintaining internal applications and scripts
  • DevOps, SRE and platform teams
  • IT administrators with automation responsibilities
  • Operations and RevOps engineers
  • Business process automation teams

Typical challenges we address

  • A long backlog of internal tools that never get prioritised next to product work
  • Manual reconciliation between SaaS systems, spreadsheets and databases that is prone to error
  • Internal tools with excessive permissions, no logging and no clear owner
  • Undocumented scripts that only one person understands

What you will be able to do

  • You use Copilot completions, chat and agent mode purposefully for your everyday development tasks.
  • You capture project knowledge in custom instructions and prompt files to improve output quality.
  • You delegate suitable issues to the coding agent and review its pull requests properly.
  • You integrate Copilot code review sensibly into your existing review process.
  • Build internal tools, bots and automations with AI agents quickly and to a solid standard.
  • Implement authentication, permissions, logging and secrets management correctly from the outset.
  • Design automations that are documented, testable and operable, so they do not depend on individual people.

Course outline

Day 1

Module 1 Copilot in the editor: completions and chat
  • Accepting, rejecting and steering inline and next edit suggestions efficiently
  • Using Copilot Chat for explanations, debugging and test generation
  • Setting context precisely with files, selections, workspace and chat variables
  • Model selection and differences between VS Code, Visual Studio and JetBrains IDEs
Module 2 Agent mode and extensions
  • Planning multi-step tasks in agent mode and executing them under control
  • Feeding terminal commands, test runs and error output into the agent loop
  • Connecting MCP servers for additional tools and data sources
  • Reviewing changes, accepting them partially or rolling them back
Module 3 Project knowledge through custom instructions
  • Writing repository-wide instructions on architecture, style and testing
  • Creating path-specific instructions and reusable prompt files
  • Combining personal and organisation-wide guidance sensibly
  • Refining instructions continuously based on output quality
Module 4 Coding agent and code review on GitHub
  • Writing issues the coding agent can implement reliably
  • Reviewing, commenting on and iterating over the agent’s pull requests
  • Using Copilot code review as an additional check in the PR process
  • Configuring the agent’s development environment with setup steps and Actions

Day 2

Module 5 Administration, policies and security
  • Licence assignment and policies at organisation and enterprise level
  • Content exclusions, model availability and public code filters
  • Using audit logs and usage metrics to steer adoption
  • Clarifying security risks, secrets and accountability for AI-generated code
Module 6 Practice lab: Internal Tools & Automation
  • Generating admin interfaces
  • Automating data reconciliation
  • Chat bots for teams
  • Automating ops runbooks
  • Generating reports and exports
  • Building agent workflows
Module 7 Data protection, quality & transfer to daily work
  • Internal tools often access employee, customer and production data: you learn to grant permissions on a least-privilege basis, keep secrets in vaults rather than code, log access and take GDPR and works council requirements into account for tools that touch employee data.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Generating admin interfaces

Create CRUD interfaces from a database schema or API with search, filters, validation, role-based permissions and an audit log, so business teams can maintain master data safely.

Automating data reconciliation

Write scripts that regularly pull data from CRM, ERP, ticketing systems and spreadsheets, reconcile it and report discrepancies, with retry logic, idempotency and clear error messages.

Chat bots for teams

Build Slack or Teams bots that answer status queries, trigger approvals, announce deployments or provide on-call information while only executing explicitly permitted actions. Every action is logged with the user ID.

Automating ops runbooks

Turn recurring operational tasks such as user management, certificate renewal or log analysis into reviewed scripts and workflows, safeguarded with a dry-run mode and logging.

Generating reports and exports

Automatically prepare regular analyses from databases and APIs as PDF, spreadsheet or email, including scheduling, parameters and traceable data sources. Manual copy-and-paste between systems disappears entirely.

Building agent workflows

Connect AI agents to tools such as the ticketing system, knowledge base and internal APIs, for example via MCP, to pre-qualify requests, gather data and prepare drafts for human approval.

Possible hands-on projects

Onboarding automation

A workflow that creates accounts in several systems for new starters, assigns groups and sends the line manager a checklist of outstanding steps.

Licence overview

An internal dashboard that pulls usage data from SaaS tools, flags unused licences and shows costs per team at a glance.

Deployment bot

A chat bot that announces deployments, summarises changes from pull requests and notifies the right people when a pipeline fails.

Prerequisites

You develop software regularly, work with Git and GitHub issues and pull requests, and use a modern IDE. You have programming experience in a language such as Python, TypeScript or Go and know the basics of APIs, databases and the command line.

Technical requirements

Your own laptop with VS Code or a JetBrains IDE, the Copilot extension installed and a GitHub account with an active Copilot licence; the coding agent requires a suitable plan.

Data protection & compliance

Internal tools often access employee, customer and production data: you learn to grant permissions on a least-privilege basis, keep secrets in vaults rather than code, log access and take GDPR and works council requirements into account for tools that touch employee data.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Tue, 1 December 2026 – Wed, 2 December 2026 Hanover Request
  • Thu, 17 December 2026 – Fri, 18 December 2026 Online Request
  • Thu, 14 January 2027 – Fri, 15 January 2027 Munich Request
  • Wed, 27 January 2027 – Thu, 28 January 2027 Online Request
  • Wed, 3 February 2027 – Thu, 4 February 2027 Stuttgart Request

Frequently asked questions

What is the difference between agent mode and the coding agent?

Agent mode runs inside your IDE: you work interactively with Copilot, see every step and approve commands. The coding agent, by contrast, works autonomously on GitHub once you assign it an issue, uses its own execution environment and opens a pull request that you then review just as you would a contribution from a colleague.

How can we make sure Copilot complies with our company policies?

At organisation and enterprise level you can enable or block specific features, models and extensions. Content exclusions keep sensitive files out of the context, and audit logs make usage traceable. During the course we show how to align these controls with data protection, information security requirements and your internal coding standards.

Is the course worthwhile if we already use Copilot?

Yes, especially then. Many teams rely on completions alone and barely touch chat, agent mode, custom instructions or the coding agent. The course shows how to use these features in a structured way, improve results with project knowledge and avoid common pitfalls. Experienced users benefit most from the sections on review and governance.

When is a custom internal tool better than an off-the-shelf product?

When a process is specific to your organisation, spans several systems or standard tools only fit after heavy customisation. AI cuts development cost considerably, but operation and maintenance remain. In the course you learn to weigh effort against benefit realistically and build tools that keep working with minimal upkeep.

How do we secure internal tools that were built quickly with AI?

With fixed guardrails: sign-in through your central identity provider, role-based permissions, no secrets in code, logging of every write action and a short review before go-live. These building blocks can be stored as a template so AI agents include them automatically in every new tool. You create exactly these templates in the course.

How much does “GitHub Copilot for Internal Tools and Automation” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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