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Data Structures with Generic Types in Python

Gain insights into array-based and linked list-based data structures, explore advanced structures like skiplists and hashing, and discover template-based collections.

4.8

96 Lessons

29h

Updated 2 months ago

Also available in

C++

Java

Python

Also available in

Python

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LEARNING OBJECTIVES

A thorough understanding of data structures and algorithms
Working knowledge of array-based, linked list-based, and blended implementations
Hands-on experience of Python interfaces, classes, and templates
Familiarity with complexity analysis of data structures and related algorithms

Learning Roadmap

96 Lessons14 Quizzes

Overview

Get familiar with data structures, their efficiency, interfaces, and mathematical basics in Python.

Introduction

The Need for Efficiency

Interfaces

Mathematical Background

The Model of Computation

Approach and Coverage

Quiz

Discussion

Array-Based Lists

Unpack the core of array-based lists, including stacks, queues, deques, and efficiency optimizations.

Array Implementation of Stack

ArrayQueue: An Array-Based Queue

ArrayDeque: Fast Deque Operations Using an Array

DualArrayDeque: Building a Deque from Two Stacks

RootishArrayStack: A Space-Efficient Array Stack

Analysis of RootishArrayStack

Quiz on Array-Based Lists

Discussion on Array-Based Lists

Exercise: Array-Based Lists

Solution: Array-Based Lists

Linked Lists

7 Lessons

Work your way through SLList, DLList, and SEList efficiency, operations, and analysis.

Skiplists

8 Lessons

Enhance your skills in efficient data structure management with skiplists' O(log n) operations.

Hash Tables

7 Lessons

Dig into hash tables, their types, hashing techniques, practical exercises, and performance discussions.

Binary Trees

5 Lessons

Simplify complex topics related to binary tree structures, their operations, and practical implementations.

Random Binary Search Trees

6 Lessons

Piece together the parts of Random Binary Search Trees, Treaps, theoretical analysis, and implementation exercises.

Scapegoat Trees

6 Lessons

Step through Scapegoat Trees, analyzing operations, performance, and optimization techniques.

Red-Black Trees

5 Lessons

Get started with red-black trees for efficient and balanced data structure operations.

10.

Heaps

6 Lessons

Break apart heaps, including binary and meldable, with their implementation and efficiency.

11.

Sorting Algorithms

9 Lessons

Grasp the fundamentals of merge-sort, quicksort, heapsort, comparison bounds, and counting-based sorting techniques.

12.

Graphs

8 Lessons

Deepen your knowledge of graph structures, their representations, traversals, and algorithms.

13.

Data Structures for Integers

4 Lessons

Investigate integer data structures like BinaryTrie, XFastTrie, and YFastTrie for efficient operations.

14.

External Memory Searching

6 Lessons

Master efficient external memory searching with B-trees, focusing on balanced depth and minimal disk access.

15.

Wrap Up

Learn how to use data structures and algorithms in Python effectively.

Conclusion

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

ABOUT THIS COURSE

Data structures and algorithms are essential in computer science since they play a crucial role in efficient information retrieval and processing, dealing with files, storing contacts on phones, social networks and web searches. In this course, you’ll learn about the array-based implementation of various linear data structures, stack, and queues. You’ll also learn about linked list-based implementation. Next, you’ll explore advanced data structures like skiplists and hashing. You’ll learn how to implement a variety of trees and graphs, and data structures related to bits of an integer. Toward the end of the course, you’ll learn the implementation of structures based on external storage. After completing this course, you’ll be able to create reusable programs with template-based collections that can efficiently analyze how to optimize the storage and retrieval of very large amounts of data. Overall, this course will enhance your productivity and performance as a software developer.

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