Python Data Structures and Algorithms

Course details

Software developers know that efficient underlying architecture is essential to the technologies we use every day. Knowledge of data structures and the algorithms which they support helps developers choose the most suitable solution for a given context, making them better programmers who stand out to their company, clients, or prospective employers. In this course, leveraging the Python programming language, instructor Robin Andrews uses a combo of visual, theoretical, and hands-on programming approaches to explain concepts in a fun and accessible way. Robin explains some of the most important data structures such as stacks, queues, and priority queues, and how these are used by search algorithms such as depth-first search, breadth-first search, and the A-star (A*) algorithm. He shows how to trace the execution of algorithms. Along the way, he provides challenges that allow you to test your new skills.

Concepts

0. Introduction

01 - Python data structures and algorithms in action
02 - What you should know

1. Pathfinding Algorithms in a Maze Game

03 - Understand the example application
04 - Navigate the GUI

2. The Stack Data Structure

05 - Understand the stack data structure
06 - Build a stack class in Python
07 - Solution - Reverse a string using a stack

3. The 2D List Data Structure

08 - Understand the 2D list data structure
09 - Represent a maze as a 2D list
10 - Read a maze from a text file
11 - Challenge - Read and display a maze from a text file
12 - Solution - Read and display a maze from a text file

4. Depth-First Search Algorithm

13 - Understand the depth-first search algorithm
14 - Visualize depth-first search on a grid
15 - Use the Grid Tracer app
16 - Code a depth-first search in Python
17 - Challenge - Trace the path of a depth-first search
18 - Solution - Trace the path of a depth-first search

5. The Queue Data Structure

19 - Understand the queue data structure
20 - Build a queue class in Python
21 - Solution - Practice queue methods

6. The Breadth-First Search Algorithm

22 - Understand the breadth-first search algorithm
23 - Visualize breadth-first search in a grid
24 - Code a breadth-first search in Python
25 - Challenge - Trace the path of a breadth-first search
26 - Solution - Trace the path of a breadth-first search

7. The Priority Queue Data Structure

27 - Understand the priority queue data structure
28 - Use the heap module to implement a priority queue
29 - Solution - Heapq methods practice

8. The A Search Algorithm

30 - Understand the A search algorithm
31 - Visualize the A algorithm
32 - Code the A algorithm in Python
33 - Challenge - Trace the path of an A search
34 - Solution - Trace the path of an A search

Conclusion

35 - Pathfinding algorithms in the course maze GUI
36 - Parting comments and what comes next