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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 patterns. You’ll learn to apply each pattern to several related problems, with a visual representation of the working of the pattern, and learn to appreciate the advantages of DP solutions over naive solutions.

After completing this course, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence.

This course is also available in JavaScript, C++, and Java—with more coming soon!

Grokking Dynamic Programming: A Deep Dive Using Python

# Statement

Given a robot located at the top-left corner of an $m \times n$ matrix, determine the number of unique paths the robot can take from start to finish while avoiding all obstacles on the matrix.

The robot can only move either down or right at any time. The robot tries to reach the bottom-right corner of the matrix.

An obstacle is marked as `1`, and an unoccupied space is marked as `0` in the matrix.

Let's solve the Unique Paths to Goal problem using Dynamic Programming.

Getting Started

0/1 Knapsack

Unbounded Knapsack

Recursive Numbers

Longest Common Substring

Palindromic Subsequence

Conclusion

Unique Paths to Goal

Statement