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Algorithmic Thinking with Python: Diving Deeper

via LinkedIn Learning

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Overview

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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.

Syllabus

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

Taught by

Robin Andrews

Reviews

4.5 rating at LinkedIn Learning based on 140 ratings

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