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Grokking Dynamic Programming Interview in JavaScript

Gain insights into dynamic programming in JavaScript with strategies developed by FAANG engineers. Practice with real-world interview questions and get interview-ready in just a few hours.

Intermediate

53 Lessons

25h

Certificate of Completion

Gain insights into dynamic programming in JavaScript with strategies developed by FAANG engineers. Practice with real-world interview questions and get interview-ready in just a few hours.
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This course includes

133 Playgrounds
44 Challenges
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Course Overview
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Course Overview

Some of the toughest questions in technical interviews require dynamic programming solutions. Dynamic programming (DP) is an advanced optimization technique applied to recursive solutions. However, DP is not a one-size-fits-all technique, and it requires practice to develop the ability to identify the underlying DP patterns. With a strategic approach, coding interview prep for DP problems shouldn’t take more than a few weeks. This course starts with an introduction to DP and thoroughly discusses five DP pa...Show More
Some of the toughest questions in technical interviews require dynamic programming solutions. Dynamic programming (DP) is an advanced optimization technique applied to recursive solutions. However, DP is not a one-size-fits-all technique, and it requires p...Show More

What You'll Learn

A deep understanding of the essential patterns behind common dynamic programming interview questions—without having to drill endless problem sets
The ability to identify and apply the underlying pattern in an interview question by assessing the problem statement
Familiarity with dynamic programming techniques with hands-on practice in a setup-free coding environment
The ability to efficiently evaluate the tradeoffs between time and space complexity in different solutions
A flexible conceptual framework for solving any dynamic programming question, by connecting problem characteristics and possible solution techniques
A deep understanding of the essential patterns behind common dynamic programming interview questions—without having to drill endless problem sets

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Course Content

1.

Getting Started

3 Lessons

Get familiar with dynamic programming essentials, ideal for coding interviews and runtime efficiency.

3.

Unbounded Knapsack

6 Lessons

Examine key strategies for solving Unbounded Knapsack, Maximum Ribbon Cut, Rod Cutting, Minimum Coin Change, and Coin Change II problems.

6.

Palindromic Subsequence

6 Lessons

Follow the process of finding, optimizing palindromic subsequences, substrings, and partitioning using dynamic programming.

7.

Conclusion

1 Lessons

Build on improved problem-solving skills and engage in further algorithm courses.

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Frequently Asked Questions

How can I improve my intuition for solving dynamic programming problems?

To develop a strong intuition for DP problems, start by solving simpler problems like Fibonacci or coin change, focusing on how subproblems overlap. Practice breaking down problems into smaller components and recognize patterns like overlapping subproblems and optimal substructure. Gradually move on to more complex problems and study different DP patterns to build understanding.

Why is dynamic programming considered more efficient than brute-force solutions?

How do I choose between memoization and tabulation in a dynamic programming problem?

What are some common mistakes to avoid when solving dynamic programming problems?

How can dynamic programming be applied in real-world applications?