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 for efficient data storage and retrieval.

Beginner

96 Lessons

29h

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

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Explanations

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Explanations

This course includes

46 Playgrounds
14 Quizzes

This course includes

46 Playgrounds
14 Quizzes

Course Overview

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 ...Show More

What You'll Learn

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

What You'll Learn

A thorough understanding of data structures and algorithms

Show more

Course Content

1.

Overview

Get familiar with data structures, their efficiency, interfaces, and mathematical basics in Python.
2.

Array-Based Lists

Unpack the core of array-based lists, including stacks, queues, deques, and efficiency optimizations.
3.

Linked Lists

Work your way through SLList, DLList, and SEList efficiency, operations, and analysis.
4.

Skiplists

Enhance your skills in efficient data structure management with skiplists' O(log n) operations.
5.

Hash Tables

Dig into hash tables, their types, hashing techniques, practical exercises, and performance discussions.
6.

Binary Trees

5 Lessons

Simplify complex topics related to binary tree structures, their operations, and practical implementations.
7.

Random Binary Search Trees

6 Lessons

Piece together the parts of Random Binary Search Trees, Treaps, theoretical analysis, and implementation exercises.
8.

Scapegoat Trees

6 Lessons

Step through Scapegoat Trees, analyzing operations, performance, and optimization techniques.
9.

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

1 Lesson

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

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