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

	Starting date	Place	Type	Course duration	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

Prerequisites

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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