Dynamic programming (DP) is often considered one of the most intimidating topics in coding interviews. It has a reputation for being abstract and counterintuitive, but it doesn't have to be.
We just published a comprehensive Dynamic Programming course on the freeCodeCamp.org YouTube channel that uses a visual-first approach to learn these complex algorithms.
Created by Sheldon, an ex-Google engineer with over 10 years of experience, this course focuses on helping you develop a visual intuition for optimization. Instead of asking you to memorize hundreds of individual problems, Sheldon teaches you to recognize the underlying patterns that connect them.
The course breaks down dynamic programming into six fundamental patterns, explaining the logic and code (using Python) for each:
Constant Transition: Learn the basics with problems like the Climbing Stairs and House Robber, where the state depends on a fixed number of previous states.
Grid Pattern: Explore 2D dynamic programming with problems like Unique Paths, learning how to build tables to solve navigation challenges.
Two Sequences: Discover how to compare strings and sequences using 2D tables, covering classics like Longest Common Subsequence and Edit Distance.
Interval DP: Tackle problems involving finding optimal substructures within intervals, such as the Longest Palindromic Subsequence.
Non-Constant Transition: Understand complex transitions where a state depends on a variable number of previous states, illustrated by the Longest Increasing Subsequence problem.
Knapsack-Like Problems: Master problems involving building specific sums or filling capacities, such as Partition Equal Subset Sum and Coin Change.
Watch the full course on the freeCodeCamp.org YouTube channel (2-hour watch).