Programming in Rust (LFD480)

Course code: LFD480

In this instructor-led course, you’ll obtain a solid understanding of idiomatic Rust and improve your developer productivity.

This course teaches you to program in idiomatic Rust, applying concepts like ownership, borrowing and lifetimes; primitive and complex types; std collection; error handling; testing programs; profiling programs; concurrency; smart pointers; using C code with FFI; using Rust with containers and Kubernetes; and deployment on multiple architectures (AMD64, ARM64, RISCV64).

3 100 EUR

3 751 EUR including VAT

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Course dates

Starting date: Upon request

Type: Virtual

Course duration: 4 days

Language: en/cz

Price without VAT: 3 100 EUR


Type Course
Language Price without VAT
Upon request Virtual 4 days en/cz 3 100 EUR Register
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Course description

This course enables you to become a confident developer in the Rust programming language. You will be able to write small system programs using OS functions; single web page applications; API clients and servers; and programs that use Rust’s concurrency features. Leveraging the rich Rust ecosystem, modules and tools, you will be able to start your own projects and engage with existing ones.

This course includes

  • Live Online (Virtual)
  • 4 days of Instructor-led class time
  • Hands-on Labs & Assignments
  • Resources & Course Manual
  • Certificate of Completion
  • Digital Badge

Target group

This course is designed for system and application programmers interested in learning the Rust language.

Course structure

  • Course Introduction
  • Rust Overview
  • My First Rust Program
  • Program Flow
  • Complex Data Types
  • Error Handling in Rust
  • Object-Oriented Programming in Rust
  • Closures
  • Iterators
  • Lifetimes
  • Crates
  • Open Source Functions
  • Unit Testing in Rust
  • Benchmarking Rust Programs
  • Smart Pointers
  • Concurrency in Rust
  • Rust capita selecta
  • Using Rust in Containers
  • Cross Compiling in Rust
  • Advanced Topics


Learners must have programming experience in another program language like C/C++, Java, JavaScript or Go.

Labs can be prepared and run on x86_64, ARM64 and RISCV64 systems. You should have at least 4GiB of RAM and 50GiB of free space. For the labs using containers and/or Kubernetes more RAM is advisable.

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