Development & technology · Node.js Back End

AI training for Node.js Back-End Developers

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.

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

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.

All 13 courses for Node.js Back-End Developers

Vibe & agentic coding (13)

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.

Prerequisites

Back-end development experience with Node.js and JavaScript or TypeScript, plus a working knowledge of databases, HTTP and Git.

Frequently asked questions

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.

Request without obligation

We will get back to you within one working day with a confirmation or an alternative suggestion.

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Total €949 plus VAT