Apr 28, 2025 · Dynamic programming study guide for coding interviews, including practice questions, techniques, time complexity, and recommended resources

A concise guide to Dynamic Programming concepts, techniques, and common patterns for algorithm design and interview preparation.

Dynamic programming is a technique to optimize algorithms by breaking a problem with overlapping sub-problems into smaller sub-problems and then combining the solutions to the sub-problems to solve the larger problem.

Contribute to siero/Dynamic-Programming-Cheat-Sheet development by creating an account on GitHub.

Feb 22, 2025 · Here is the collection of the Top 50 list of frequently asked interview questions on Dynamic Programming. Problems in this Article are divided into three Levels so that readers can practice according to the difficulty level step by step.

Aug 8, 2022 · Given n coins two players A and B are playing a game with alternate turns. In each turn player can either choose first coin or last coin. Find maximum sum of coins player A can get.

Mar 21, 2024 · Welcome to my Dynamic Programming (DP) Problem Sheet! This is an ever-growing list of DP problems from LeetCode. Dynamic programming is a powerful technique used to solve optimization problems by breaking them down into simpler subproblems and storing their solutions to avoid redundant computations.

A summary of the essentials for solving dynamic programming problems in coding interviews.

Cheat-Sheet for Dynamic Programming Written by Marcelo Siero, based on UCSC’s class on Algorithm Design taught by Prof. Dmitris Achlioptas, with ideas passed on by Greg Levin. Dynamic Programming is approached as a DAG (Directed Acyclic Graph) of sub-problems.

In this cheat-sheet we provide a short-hand for the solutions to a wide-variety problems that are solved with the techniques of dynamic programming. {\bf \Large Template for Solution Short-Hand }