Dynamic Programming Tutorial

This course is for developers who can write recursion and loops comfortably but freeze when an interview question says "find the minimum" or "count the number of ways". If you have met a solution that fills a grid of numbers and could not explain why it works, the four lessons here are written for you. You should be happy with Python functions, lists and dictionaries; if arrays and strings still feel shaky, start with Arrays and Strings.

You will learn to recognise when a problem is repeating work, to fix it with a cache (memoization), to build the same answer bottom-up in a table (tabulation), and to read a table as a story instead of a wall of digits. Then you will apply the method to three families of problems that cover a large share of what interviewers ask: minimum or count over amounts (coin change), comparing two sequences (longest common subsequence and edit distance) and choose-or-skip decisions under a limit (0/1 knapsack).

The lessons build in order. Lesson one explains the idea with a recursion that visibly wastes work. Lesson two replaces the recursion with a loop. Lesson three solves the classics with fresh scenarios, and lesson four shrinks the memory they use and gives you a repeatable way to think aloud in an interview. Every Python snippet was executed and the printed output is exactly what it produced. Pair it with Data Structures when you want more practice with the containers DP tables are built from.