Training course · GitHub Copilot · Node.js Back End

GitHub Copilot for Node.js Back-End Developers

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

“GitHub Copilot for Node.js Back-End Developers” is designed for roles such as Back-end developers using Express, Fastify or NestJS, Full-stack developers responsible for API layers and Developers building serverless functions and integration services and shows step by step how to use GitHub Copilot productively, safely and transparently in Node.js Back End – from the fundamentals to advanced workflows.

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.

For many teams, Node.js is the backbone of REST and GraphQL APIs, real-time services, serverless functions and integration layers. Typical back-end work follows recurring patterns: routes and validation, database access with Prisma, Drizzle or TypeORM, authentication, error handling, logging and tests against real dependencies. AI coding assistants and agents handle these patterns reliably once they understand the project architecture. They generate endpoints from OpenAPI specifications, migrate Express applications to modular structures, write integration tests with Testcontainers and analyse memory leaks or event-loop-blocking operations. This course teaches you to use agents in a way that keeps security, observability and maintainability firmly intact.

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?

  • Back-end developers using Express, Fastify or NestJS
  • Full-stack developers responsible for API layers
  • Developers building serverless functions and integration services
  • Software architects designing Node.js-based microservices

Typical challenges we address

  • Organically grown Express apps with no clear layering and scattered error handling
  • Insufficient input validation and weaknesses in authentication and authorisation
  • Performance issues caused by blocking code or memory leaks that are hard to diagnose
  • Missing integration tests against databases, queues and external APIs

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.
  • Have AI agents build endpoints, data layers and integration tests that fit your Node.js architecture.
  • Use AI to analyse performance problems, memory leaks and security weaknesses in the back end.
  • Define guardrails so that generated back-end code meets your standards for validation, logging and error handling.

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: Node.js Back End
  • API endpoints from specifications
  • Database access and migrations
  • Integration tests with Testcontainers
  • Restructuring Express applications
  • Analysing performance and memory leaks
  • Security hardening
Module 7 Data protection, quality & transfer to daily work
  • Back ends often process personal data: production data, logs and database dumps should never go into prompts unfiltered, and credentials from environment variables must stay excluded. Vet new npm dependencies for supply-chain risk and licensing, and for critical services take the security requirements of NIS2 into account.
  • 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

API endpoints from specifications

From an OpenAPI or GraphQL schema, the agent generates routes or resolvers, validation with Zod or class-validator, service layers and consistent error responses – all matching your existing project structure.

Database access and migrations

The AI models schemas for Prisma, Drizzle or TypeORM, writes migrations, optimises queries with indexes and transactions and explains the impact on existing data before rollout.

Integration tests with Testcontainers

The assistant writes tests that spin up real databases, Redis or message brokers in containers, seed data and exercise API endpoints end to end with Supertest against realistic dependencies.

Restructuring Express applications

Monolithic Express projects are split into modules with controllers, services and repositories, middleware is standardised and callback code moved to async/await – backed by existing and new tests.

Analysing performance and memory leaks

The AI interprets heap snapshots, profiler output and logs, identifies operations blocking the event loop and proposes fixes such as streams, worker threads or caching.

Security hardening

The agent reviews authentication flows using JWTs or sessions, adds rate limiting, secure HTTP headers and input validation and checks the code against the OWASP API security risks.

Possible hands-on projects

Webhook relay service

A Fastify service that receives webhooks from various SaaS providers, verifies signatures, queues events and forwards them to internal systems with retry logic.

Job queue with dashboard

A background-processing service built on BullMQ and Redis, with retry strategies, a monitoring UI and integration tests. Failed jobs can be inspected and retried directly from the UI.

API gateway prototype

A lean gateway service with authentication, rate limiting, request logging and routing to several back-end services, developed entirely by an AI agent.

Prerequisites

You develop software regularly, work with Git and GitHub issues and pull requests, and use a modern IDE. Back-end development experience with Node.js and JavaScript or TypeScript, plus a working knowledge of databases, HTTP and Git.

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

Back ends often process personal data: production data, logs and database dumps should never go into prompts unfiltered, and credentials from environment variables must stay excluded. Vet new npm dependencies for supply-chain risk and licensing, and for critical services take the security requirements of NIS2 into account.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Thu, 3 December 2026 – Fri, 4 December 2026 Munich Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Online Request
  • Tue, 15 December 2026 – Wed, 16 December 2026 Stuttgart Request
  • Thu, 21 January 2027 – Fri, 22 January 2027 Online Request
  • Tue, 2 February 2027 – Wed, 3 February 2027 Berlin 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.

Is the course suitable for both NestJS and Express?

Yes. We work with framework-neutral principles such as layering, validation and testability, and show with examples how to capture the conventions of Express, Fastify or NestJS in instruction files. That way the assistant generates code that fits your framework and your project structure rather than generic boilerplate.

How do I stop the AI from producing insecure back-end code?

Through clear rules, automated checks and critical review. On the course you define security rules for validation, authentication and data access, plug in static analysis and dependency scanning, and learn to spot typical weaknesses in generated code, such as missing authorisation checks or unsafe queries.

How much does “GitHub Copilot for Node.js Back-End Developers” 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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