Dynamic Programming Ruby, Coding Interviews and Applications
- Development
- Feb 04, 2025

Dynamic Programming Ruby, Coding Interviews and Applications, available at $59.99, has an average rating of 4.8, with 41 lectures, 1 quizzes, based on 21 reviews, and has 186 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 Ruby 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 Ruby, Coding Interviews and Applications
Summary
Title: Dynamic Programming Ruby, Coding Interviews and Applications
Price: $59.99
Average Rating: 4.8
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
Who Should Attend
Target Audiences
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/DynamicProgrammingInRuby
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 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

James Cutajar
Software Developer, Author, Instructor
Rating Distribution
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
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