Skills you'll gain

Specialization - 5 course series

Through over 20 hands-on coding projects like building a Rust chatbot, containerizing a web service, developing a Linux automation script, or optimizing a machine learning pipeline, learners will gain authentic, portfolio-ready experience applying their Rust skills to tackle real-world systems programming problems designed by experts at Duke University.

While a fundamental knowledge of Rust is expected, you should ideally be comfortable with the basics of data structures and algorithms, and have a working understanding of databases and data processing. Familiarity with SQL, the command line, and version control with git is advantageous. This four-week course focuses on leveraging Rust to create efficient, safe, and concurrent data processing systems. The journey begins with a deep dive into Rust's data structures and collections, followed by exploring Rust's safety and security features in the context of data engineering. In the subsequent week, you'll explore libraries and tools specific to data engineering like Diesel, async, Polars, and Apache Arrow, and learn to interface with data processing systems, REST, gRPC protocols, and AWS SDK for cloud-based data operations. The final week focuses on designing and implementing full-fledged data processing systems using Rust. By the end of this course, you will be well-equipped to use Rust for handling large-scale data engineering tasks, solving real-world problems with efficiency and speed. The hands-on labs and projects throughout this course will ensure you gain practical experience, putting your knowledge into action. This course is your gateway to mastering data engineering with Rust, preparing you for the next level in your data engineering journey.

Data Engineering with Rust

Rust for DevOps

Python and Rust with Linux Command Line Tools

Rust for Large Language Model Operations (LLMOps)