Foundations of Algorithmic Thinking with Python

Course details

The word “algorithm,” at one time the sole province of mathematics and computer science, has entered the modern vernacular because, for better or worse, algorithms have never been more important or more impactful in daily life. If you’re a developer, you need to be familiar with a wide range of algorithmic thinking in order to be able to solve new problems as they present themselves. If you’re already familiar with Python, becoming more versed in algorithmic thinking is a great way to increase your value as a developer. In this course, Robin Andrews explains how Python, because of its clarity and expressiveness, is the ideal tool for exploring algorithmic thinking. He shows you tools to help you understand the flow of algorithms, explains the brute force approach to solving algorithms, details the concepts of time and space complexity with regard to algorithm analysis, the decrease and conquer strategy, and much more.

Concepts

0. Introduction

01 - Importance of algorithmic thinking
02 - What you should know

1. Warm Up

03 - Challenge - 100 doors
04 - Solution - 100 doors
05 - FizzBuzz

2. Tools to Help Understand the Flow of Algorithms

06 - Tracing algorithms using an online visualization tool
07 - Tracing algorithms using code or a debugger
08 - Algorithm animations
09 - Pseudocode
10 - Using a whiteboard to explore algorithms

3. Brute Force Algorithms

11 - Introduction to brute force algorithms
12 - Linear search
13 - Selection Sort introduction
14 - Challenge - Selection Sort in Python
15 - Solution - Selection Sort in Python

4. Analysis of Time-Space Complexity

16 - Introduction to analysis of time-space complexity
17 - Challenge - Big-O notation practice
18 - Solution - Big-O notation practice
19 - Examples of time complexity with Python
20 - Memory considerations when implementing algorithms

5. Greedy Algorithms

21 - Introduction to greedy algorithms
22 - Introduction to the change making problem
23 - Solution to the change making problem
24 - Dijkstra's algorithm
25 - Challenge - Dijkstra's algorithm
26 - Solution - Dijkstra's algorithm
27 - Dijkstra's algorithm - Python implementation

6. Decrease and Conquer

28 - Ferrying soldiers
29 - Introduction to decrease and conquer
30 - Binary search
31 - Challenge - Binary search
32 - Solution - Binary search

Conclusion

33 - Exploring algorithmic thinking with Python

Foundations of Algorithmic Thinking with Python

Authors

Robin Andrews