Data Engineering with Rust (Coursera)

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.
This course is part of the Rust Programming Specialization.

Syllabus

Rust Data Structures: Collections
In this first week, we will delve into Rust's powerful and flexible data structures. You'll gain insights into different types of sequences, maps, and sets, discovering their distinctive characteristics and potential use cases. Through hands-on exercises and projects, you'll apply these concepts in practical scenarios. This includes creating a Fruit Salad CLI with a variety of sequences, comparing languages using both HashMap and BTreeMap, managing unique fruits with HashSet and BTreeSet, and prioritizing data using a Binary Heap. These experiences will equip you with a robust understanding of how to use Rust data structures effectively for data organization and manipulation, forming a vital foundation for the weeks ahead.

Safety, Security and Concurrency with Rust
This week, you will delve deep into the safety features and security principles that make Rust a powerful and reliable language for systems programming. You'll learn how to prevent data races, manage memory effectively to avoid leaks, safely interoperate with C libraries using Rust's Foreign Function Interface (FFI), and build robust concurrent applications leveraging Rust's unique mechanisms for handling mutable and immutable data. Through exploring automatic bounds checking and safe transmutes, you will learn to avoid common errors and undefined behaviors that are prevalent in other languages. To apply what you've learned, you will be tasked with a series of hands-on exercises that demonstrate these principles in real-world scenarios. You'll create a multi-threaded web server, a command-line application that processes diverse types of user input, and systems that would typically be vulnerable to bugs in other languages but remain secure due to Rust's inherent safety mechanisms. Through these exercises, you will gain a concrete understanding of how Rust's safety features lead to more secure, robust, and efficient code.

Rust Data Engineering Libraries and Tools
This week, you will delve deeper into the Rust ecosystem by exploring various libraries and tools specific to data engineering. You will learn how to process CSV and Parquet files, and make use of Rust's async capabilities to build efficient web scrapers and API consumers. Also, you'll get acquainted with popular data processing libraries like Polars and Apache Arrow. Furthermore, you'll discover how Rust interfaces with data processing systems for message passing, how it deals with REST and gRPC protocols, and the methods of integrating with AWS SDK for cloud-based data operations. Each project is designed to highlight the efficiency, safety, and concurrent processing capabilities of Rust in handling large-scale data engineering tasks. With a focus on hands-on practice, this week aims to equip you with the skills to solve real-world data engineering problems using Rust.

Designing Data Processing Systems in Rust
This week, you will learn how to design and implement data storage solutions and pipelines using Rust, focusing on leveraging Rust's unique capabilities to manage storage technologies effectively. You'll explore strategies for constructing robust data processing solutions and migrating existing warehousing and processing systems to more efficient Rust-oriented solutions. A significant emphasis will be placed on understanding and utilizing key Rust libraries for data processing and mastering best practices for error handling in Rust to enhance system resilience and reliability. You will apply your knowledge by working on a series of practical assignments that involve creating a Rust-based data pipeline, migrating a simple data processing system to Rust, and utilizing Rust libraries to improve a sample data processing scenario. You'll also handle simulated errors in a Rust-based data processing environment, which will help solidify your understanding and application of Rust's error handling mechanisms.