Oreilly – Grokking Data Structures 2024-7

Grokking Data Structures course. This course will help you to easily understand important and widely used concepts of data structures. Using engaging examples, true stories, and hundreds of illustrations and diagrams, this course guides you from the basics to advanced concepts.

What you will learn

• Fast lookups using hash tables
• Trees and Binary Search Trees (BSTs) for organizing data
• Using graphs to model complex data
• The best data structures for a coding challenge
• Understand the most important and commonly used data structures.
• Identify where data structures are most effective.
• Choose the best data structure solution for a coding challenge.
• Understand the compromises of data structures and avoid disasters.
• Implement primitive data sets such as arrays, linked lists, stacks, and prioritized queues.
• Use trees and binary search trees (BSTs) to organize data.
• Use graphs to model relationships and learn about complex data.
• Search efficiently by key using hash tables and hash functions.
• Argue the time and memory requirements of operations on data structures.

This course is suitable for people who

• They know the basics of Python.
• Great companion for Grokking Algorithms!

Grokking Data Structures course specifications

• Publisher:  Oreilly
• Translation: Marcello La Rocca
• Training level: beginner to advanced
• Training duration: 7 hours and 19 minutes

Course headings

• Chapter 1. Introducing data structures: Why you should learn about data structures
• Chapter 2. Static arrays: Building your first data structure
• Chapter 3. Sorted arrays: Searching faster, at a price
• Chapter 4. Big-O notation: A framework for measuring algorithm efficiency
• Chapter 5. Dynamic arrays: Handling dynamically sized datasets
• Chapter 6. Linked lists: A flexible dynamic collection
• Chapter 7. Abstract data types: Designing the simplest container—the bag
• Chapter 8. Stacks: Piling up data before processing it
• Chapter 9. Queues: Keeping information in the same order as it arrives
• Chapter 10. Priority queues and heaps: Handling data according to its priority
• Chapter 11. Binary search trees: A balanced container
• Chapter 12. Dictionaries and hash tables: How to build and use associative arrays
• Chapter 13. Graphs: Learning how to model complex relationships in data

Course images

Sample video of the course

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