Algorithmic Thinking with Python: Diving Deeper

Get familiar and competent with a wide range of algorithmic thinking skills, so you can solve new problems as they present themselves in a constantly changing world.

Introduction

• Exploration of algorithmic thinking
• Use GitHub Codespaces with this course

1. Warmup

• The two-sum interview problem
• The two-sum interview problem solution
• Number placement puzzle

2. Divide and Conquer

• Triominoes puzzle
• Triominoes puzzle solution
• Introduction to divide and conquer
• Quicksort introduction
• Implementing Quicksort in Python
• Challenge: Implementing Fibonacci function in Python
• Solution: Implementing Fibonacci function in Python

3. Transform and Conquer

• Coins on a star puzzle
• Coins on a star puzzle solution
• Introduction to transform and conquer
• Presort for mode finding
• Number placement puzzle revisited
• Challenge: Implement number puzzle solution in Python
• Solution: Implement number puzzle solution in Python

4. Dynamic Programming

• Introduction to dynamic programming
• Top-down dynamic programming example
• Bottom-up dynamic programming example
• The knapsack problem: Theory
• The knapsack problem: Python implementation
• Challenge: The knapsack problem
• Solution: The knapsack problem

5. Hash Tables

• What are hash tables?
• Python code for hash tables
• Python dictionaries
• Two-sum problem revisited
• Challenge: Ransom note
• Solution: Ransom note

Conclusion

• Next steps