Online Course

Introducing Data Structures in Python

This course is a practical and conceptual introduction to data structures using Python, designed as a natural follow-up to Introducing Algorithms in Python. Rather than focusing on low-level implementations or abstract theory, the course emphasizes how data is organized, why structure matters, and how structure affects performance and problem-solving.

You’ll begin by revisiting the idea of data as collections and explore Python lists as everyday sequences. From there, you’ll move to rule-based linear structures such as stacks and queues, learning how access restrictions shape behavior and use cases. The course then shifts to fast, non-linear lookup structures—sets and dictionaries—highlighting how hashing enables efficient membership testing and key-value access.

Finally, you’ll explore trees, the first truly hierarchical structure in the course, where data branches rather than lines up. You’ll learn tree terminology, binary trees, classic traversals, and how tree shape and depth impact efficiency. Throughout the course, examples are drawn from real-world programming and data science scenarios, with performance explained intuitively rather than mathematically.

The course concludes with a synthesis lesson that ties all structures together, helping you develop a data-scientist’s mindset for choosing data structures based on problem requirements, access patterns, and performance trade-offs.

By the end of the course, you won’t just know what data structures are—you’ll understand how to think with them.