Data Structures & Algorithms in Python

Course

Learn the skills technical interviewers expect you to know—efficiency, common algorithms, manipulating popular data structures, and how to explain a solution.

Last Updated March 7, 2022

Prerequisites:

No experience required

Last Updated March 7, 2022

Prerequisites:

No experience required

Course Lessons

Lesson 1

Introduction and Efficiency

Begin the section on data structures and algorithms, including Python and efficiency practice.

Lesson 2

List-Based Collections

Learn the definition of a list in computer science, and see definitions and examples of list-based data structures, arrays, linked lists, stacks, and queues.

Lesson 3

Searching and Sorting

Explore how to search and sort with list-based data structures, including binary search and bubble, merge, and quick sort. Learn how to use recursion.

Lesson 4

Maps and Hashing

Understand the concepts of sets, maps (dictionaries), and hashing. Examine common problems and approaches to hashing, and practice with examples.

Lesson 5

Trees

Learn the concepts and terminology associated with tree data structures. Investigate tree types, such as binary search trees, heaps, and self-balancing trees.

Lesson 6

Graphs

Examine the theoretical concept of a graph and understand common graph terms, coded representations, properties, traversals, and paths.

Lesson 7

Case Studies in Algorithms

Explore famous computer science problems, specifically the Shortest Path Problem, the Knapsack Problem, and the Traveling Salesman Problem.

Lesson 8

Technical Interviewing Techniques

Learn about the “algorithm” for answering common technical interviewing questions. Practice and get tips for giving interviewers what they’re looking for.

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Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

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