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Dynamic Programming Python, Coding Interviews Applications

  • Development
  • Feb 28, 2025
SynopsisDynamic Programming Python, Coding Interviews & Applicati...
Dynamic Programming Python, Coding Interviews Applications  No.1

Dynamic Programming Python, Coding Interviews & Applications, available at $79.99, has an average rating of 4.6, with 41 lectures, 1 quizzes, based on 89 reviews, and has 828 subscribers.

You will learn about Recognize a problem that can be solved using Dynamic Programming Come up with both a top down and bottom up Dynamic Programming solution using Python Use Dynamic Programming for coding interview puzzles and practical applications Improve your problem-solving skills and become a better developer Revise your recursion knowledge This course is ideal for individuals who are Self taught developers who are looking to up their game and become better developers or Experienced developers wanting to learn how to apply Dynamic Programming to solve certain classes of problems or Developers wanting to prepare for an upcoming coding interview or University students struggling with Dynamic Programming It is particularly useful for Self taught developers who are looking to up their game and become better developers or Experienced developers wanting to learn how to apply Dynamic Programming to solve certain classes of problems or Developers wanting to prepare for an upcoming coding interview or University students struggling with Dynamic Programming.

Enroll now: Dynamic Programming Python, Coding Interviews & Applications

Summary

Title: Dynamic Programming Python, Coding Interviews & Applications

Price: $79.99

Average Rating: 4.6

Number of Lectures: 41

Number of Quizzes: 1

Number of Published Lectures: 41

Number of Published Quizzes: 1

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

  • Recognize a problem that can be solved using Dynamic Programming
  • Come up with both a top down and bottom up Dynamic Programming solution using Python
  • Use Dynamic Programming for coding interview puzzles and practical applications
  • Improve your problem-solving skills and become a better developer
  • Revise your recursion knowledge
  • Who Should Attend

  • Self taught developers who are looking to up their game and become better developers
  • Experienced developers wanting to learn how to apply Dynamic Programming to solve certain classes of problems
  • Developers wanting to prepare for an upcoming coding interview
  • University students struggling with Dynamic Programming
  • Target Audiences

  • Self taught developers who are looking to up their game and become better developers
  • Experienced developers wanting to learn how to apply Dynamic Programming to solve certain classes of problems
  • Developers wanting to prepare for an upcoming coding interview
  • University students struggling with Dynamic Programming
  • Have you ever wondered what makes a good developer? Why it is that big tech companies are increasingly asking candidates to solve challenging coding puzzles in interviews? Or why you should bother to learn about complicated algorithms?

    With regards to technical skills a good developer has an understanding of computer science and knows when to apply this knowledge. Tech companies know that if someone has a good grasp of these fundamentals, she will likely be fine learning any programming language, using any new tool and solving a wide range of programming problems. As a developer comprehending data structures and algorithms you’ll be better equipped to tackle some of the more difficult problems both in your day-to-day job and for coding interviews.

    Dynamic Programming is a topic in data structures and algorithms. It covers a method (the technical term is “algorithm paradigm”) to solve a certain class of problems. In this course we will go into some detail on this subject by going through various examples. The course is designed not to be heavy on mathematics and formal definitions. Instead you will learn through practical everyday programming algorithms and through some coding interview puzzles. We present a method to recognize problems that can be solved using dynamic programming and then build an efficient solution through small gradual steps.

    In addition, you will also learn how to gamble professionally, how to be an air traffic controller and how to become a serious writer.*

    *Not really… but hey it’s hard to make Dynamic Programming sound exciting

    All code in this course can be found on github, username/project: cutajarj/DynamicProgrammingInPython

    At the end of the course we have a small coding exercise to test your knowledge.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: Useful links and resources

    Chapter 2: Understanding Recursion

    Lecture 1: Introduction to recursion

    Lecture 2: More Recursion

    Chapter 3: Counting Derangements

    Lecture 1: Whats a Derangement?

    Lecture 2: Coming up with a Recurrence Relation

    Lecture 3: Recursive code walkthrough

    Lecture 4: Top Down Solution

    Lecture 5: Top Down code walkthrough

    Lecture 6: Bottom Up Solution

    Lecture 7: Bottom Up code walkthrough

    Lecture 8: Optimization and code walkthrough

    Chapter 4: Aircraft Spacing

    Lecture 1: Solving Air Traffic

    Lecture 2: Defining a solution recursively

    Lecture 3: Recursive code walkthrough

    Lecture 4: Top Down Solution

    Lecture 5: Top Down code walkthrough

    Lecture 6: Bottom Up Solution

    Lecture 7: Bottom Up code walkthrough

    Lecture 8: Optimization and code walkthrough

    Chapter 5: Maximum Sub Array

    Lecture 1: How are maximum sub arrays useful?

    Lecture 2: Recurrence Relation

    Lecture 3: Recursive code walkthrough

    Lecture 4: Top Down Solution and code walkthrough

    Lecture 5: Bottom Up Solution and code walkthrough

    Lecture 6: Optimization and code walkthrough

    Chapter 6: Text Justification

    Lecture 1: How to make paragraphs look pretty

    Lecture 2: Solving Recursively

    Lecture 3: Recursive code walkthrough

    Lecture 4: Bottom Up Solution

    Lecture 5: Bottom Up code walkthrough

    Lecture 6: Optimization

    Lecture 7: Optimization and code walkthrough

    Chapter 7: String Distance

    Lecture 1: Distance between Strings

    Lecture 2: Solving Recursively

    Lecture 3: Recursive code walkthrough

    Lecture 4: Top Down Solution and code walkthrough

    Lecture 5: Bottom Up Solution

    Lecture 6: Bottom Up code walkthrough

    Lecture 7: Optimization and code walkthrough

    Chapter 8: Final Course Exercise

    Lecture 1: Well done!

    Instructors

  • Dynamic Programming Python, Coding Interviews Applications  No.2
    James Cutajar
    Software Developer, Author, Instructor
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  • 3 stars: 5 votes
  • 4 stars: 23 votes
  • 5 stars: 59 votes
  • Frequently Asked Questions

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