HomeCoursesDynamic Programming in Python: Optimizing Programs for Efficiency

4.6

Intermediate

Updated 5 months ago

Dynamic Programming in Python: Optimizing Programs for Efficiency

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

Content

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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 varying difficulty so you can practice a wide range of problems. By the time you’ve completed this course, you will be able to utilize dynamic programming in your own projects.

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.

Chapter 4: Practice Problems

17 Lessons

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

Solving Sudoku and the 8-Queens Puzzle as Constraint Satisfaction

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Personalized Interview Prep

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Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

Code Feedback

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