Data Engineering with Rust

Duke University applies Rust to data-processing work through collections, concurrency and the libraries used in a processing system. Safety concerns connect with design choices rather than remain a separate syntax topic. It suits intermediate programmers who want to investigate how Rust’s constraints affect a data workflow and the way that workflow handles failures.

What you will learn

• Explore Rust collections for data processing.
• Connect concurrency with safety considerations.
• Design workflows using data-engineering libraries.

Who this suits

Intermediate programming experience, Git and a text editor are recommended; Python experience is also useful.

Before you enroll

Install a suitable Rust toolchain and check the edition and crate versions used in demonstrations. Compiler diagnostics, dependency APIs and editor setup can differ from recorded examples. Run code in a project you control and inspect unfamiliar dependencies. Allow time for exercises and debugging beyond video runtime. A completion certificate describes course participation, not independent proof of programming proficiency.

Coursera offers paid enrollment or subscription access. Check the enrollment screen for assessment and certificate terms, trials and any financial-aid options. Provider access terms can change; review them before paying.

Put it into practice

Design a small file-processing pipeline and specify how invalid records, partial failures and concurrent work should be handled before writing the implementation.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

How YellowCourse describes and checks learning resources.