Training course · GitHub Copilot · Rust

GitHub Copilot for Rust 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 Rust Developers” is designed for roles such as Rust developers working on systems and back-end projects, C and C++ developers moving to Rust or porting modules and Embedded and IoT developers using Rust and shows step by step how to use GitHub Copilot productively, safely and transparently in Rust – 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.

Rust is gaining ground wherever memory safety and performance have to go hand in hand: in systems software, embedded projects, network services, WebAssembly and security-critical components. The learning curve is steep – ownership, lifetimes, traits and async runtimes challenge even experienced developers. AI coding assistants and agents prove to be patient sparring partners here: they explain borrow checker errors, suggest suitable ownership structures, write tests and property-based tests, port C or C++ modules incrementally and work through Clippy lints. Because the compiler gives very precise feedback, agents can iterate all the way to compiling, safe code. This course teaches you to exploit that feedback loop and to scrutinise unsafe code with particular care.

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?

  • Rust developers working on systems and back-end projects
  • C and C++ developers moving to Rust or porting modules
  • Embedded and IoT developers using Rust
  • Security and platform teams focused on memory safety

Typical challenges we address

  • Hard-to-understand borrow checker and lifetime errors
  • Complex trait hierarchies, generics and async code with Tokio
  • Laborious porting of existing C or C++ codebases across FFI boundaries
  • Handling unsafe blocks responsibly and justifying each one

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.
  • Use AI agents as sparring partners for ownership, lifetimes, traits and async Rust.
  • Generate tests, ports and services and verify them with the compiler, Clippy and Miri.
  • Systematically assess generated unsafe and FFI code for memory safety.

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: Rust
  • Understanding and fixing compiler errors
  • Tests and property-based tests
  • Porting C and C++ modules
  • Async services with Tokio
  • Clippy and idiomatic code
  • Reviewing unsafe code
Module 7 Data protection, quality & transfer to daily work
  • Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted models.
  • 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

Understanding and fixing compiler errors

The assistant explains borrow checker and lifetime errors in plain language, deliberately proposes alternative ownership structures such as references, Rc or cloning, and iterates with cargo check until the build is clean.

Tests and property-based tests

The AI writes unit and integration tests, doc tests and property-based tests with proptest that check invariants over many generated inputs, uncovering edge cases in parsers or algorithms.

Porting C and C++ modules

Existing code is moved to Rust module by module, FFI bindings are created with bindgen or cbindgen and behaviour is safeguarded by shared tests run against the old and new implementations.

Async services with Tokio

Specifications become HTTP or gRPC services built with Axum or Tonic, including structured error types, graceful shutdown, tracing and sensible handling of cancellation and timeouts.

Clippy and idiomatic code

Clippy lints are worked through systematically, error handling standardised with thiserror or anyhow, and iterators, pattern matching and traits used idiomatically. Existing tests safeguard every change.

Reviewing unsafe code

The agent inventories unsafe blocks, documents their safety invariants, proposes safe alternatives and runs Miri to detect undefined behaviour. Each justification is recorded as a SAFETY comment in the code.

Possible hands-on projects

Fast log parser

A Rust CLI that streams large log files, detects patterns with regular expressions and outputs statistics – with benchmarks comparing it against a scripting-language version.

Axum microservice

A small REST service using Axum, SQLx, structured tracing and integration tests, planned and implemented end to end by an AI agent.

WebAssembly module

A compute-heavy function, such as image processing or validation, packaged as a WebAssembly module with wasm-bindgen and embedded in a simple web page.

Prerequisites

You develop software regularly, work with Git and GitHub issues and pull requests, and use a modern IDE. Basic Rust experience with Cargo, ownership and traits, plus experience in at least one other systems or back-end language.

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

Rust is often used in security-critical components for which the Cyber Resilience Act sets requirements on vulnerability handling and SBOMs. Check new crates for vulnerabilities and licences with cargo-audit or cargo-deny, and treat proprietary systems code as confidential when using cloud-hosted models.

Suggested dates

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

  • Wed, 25 November 2026 – Thu, 26 November 2026 Online Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Salzburg Request
  • Wed, 16 December 2026 – Thu, 17 December 2026 Online Request
  • Tue, 12 January 2027 – Wed, 13 January 2027 Bremen Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Online Request
  • Thu, 28 January 2027 – Fri, 29 January 2027 Augsburg 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.

Can AI help me get started with Rust?

Very much so. AI assistants explain compiler errors patiently and in the context of your own code, show alternative approaches and explain why the borrow checker rejects a construct. The key is to understand the explanations rather than accept suggestions blindly, so the course relies on hands-on exercises in which you work out solutions together with the AI.

How reliable are AI ports from C++ to Rust?

They work well for clearly bounded modules when behaviour is protected by tests. The tricky parts are pointer arithmetic, shared mutable state or undefined behaviour in the original. On the course you learn to port incrementally, run differential tests against the old implementation and keep unsafe code to a deliberate minimum.

How much does “GitHub Copilot for Rust 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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