Development & technology · Rust

AI training for Rust Developers

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.

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

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.

All 10 courses for Rust Developers

Vibe & agentic coding (10)

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.

Prerequisites

Basic Rust experience with Cargo, ownership and traits, plus experience in at least one other systems or back-end language.

Frequently asked questions

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.

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