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Dynamic Programming in Python: Optimizing Programs for Efficiency
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Learn about dynamic programming in Python, delve into recursion basics, explore advanced DP techniques, and discover practical coding challenges to optimize algorithms for real-world applications.

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Overview

Dynamic programming is something every developer should have in their toolkit. It allows you to optimize your algorithm with respect to time and space — a very important concept in real-world applications. In this course, you’ll start by learning the basics of recursion and work your way to more advanced DP concepts like Bottom-Up optimization. Throughout this course, you will learn various types of DP techniques for solving even the most complex problems. Each section is complete with coding challenges of...Show More

Dynamic programming is something every developer should have in their toolkit. It allows you to optimize your algorithm with res...Show More

Content

47 Lessons3 Quizzes16 Challenges

Chapter 1: From Recursion to Dynamic Programming

13 Lessons

Get familiar with transitioning from recursion to dynamic programming and optimizing algorithms efficiently.

Introduction

What is Recursion?

Thinking Recursively

The Fibonacci Numbers

Challenge: Find All Permutations of a String

Solution Review: Find All Permutations of a String

Challenge: Place N Queens on an NxN Chessboard

Solution Review: Place N Queens on an NxN Chessboard

Is Plain Recursion Good Enough?

What is Dynamic Programming?

Approaches of Dynamic Programming

Where to Use Dynamic Programming

Quiz

Chapter 2: Top-Down Dynamic Programming with Memoization

7 Lessons

Get started with efficient top-down dynamic programming using memoization techniques for optimization.

What is Memoization?

The Fibonacci Numbers Algorithm with Memoization

Challenge: The Staircase Problem

Solution Review: The Staircase Problem

Challenge 2: The Knapsack Problem

Solution Review: The Knapsack Problem

Quiz

Chapter 3: Bottom-Up Dynamic Programming with Tabulation

10 Lessons

Work your way through bottom-up dynamic programming, tabulation, optimization, and practical problem-solving.

Limitations of Top-Down Dynamic Programming

What is Tabulation?

The Fibonacci Numbers Algorithm with Tabulation

Optimizing the Fibonacci Numbers Algorithm

Challenge: The Catalan Numbers

Solution Review: The Catalan Numbers

Challenge 2: Longest Common Substring

Solution Review: Longest Common Substring

Top-Down vs Bottom-Up

Quiz

Chapter 4: Practice Problems

17 Lessons

Apply your skills to solve diverse dynamic programming challenges efficiently and enhance problem-solving techniques.

Challenge: Number of Ways to Represent N Dollars

Solution Review: Number of Ways to Represent N Dollars

Challenge: The Rod Cutting Problem

Solution Review: The Rod Cutting Problem

Challenge: Weighted Scheduling Problem

Solution Review: Weighted Scheduling Problem

Challenge: The Matrix Chain Multiplication

Solution Review: The Matrix Chain Multiplication

Challenge: The Traveling Salesman Problem

Solution Review: The Traveling Salesman Problem

Challenge: Longest Common Subsequence

Solution Review: Longest Common Subsequence

Challenge: Longest Palindromic Subsequence

Solution Review: Longest Palindromic Subsequence

Challenge: The Edit Distance Problem

Solution Review: The Edit Distance Problem

Conclusion

Solving Sudoku and the 8-Queens Puzzle as Constraint Satisfaction

Project

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

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