Dynamic Programming Algorithms

#2 - Climbing Stairs

#3 - House Robber

#4 - Decode Ways

#5 - Longest Common Subsequence

#6 - 0/1 Knapsack Problem

#7 - Target sum

#8 - Partion Equal Subset Sum

#13 - Regular Expression Matching

• Computer Science students
• Anyone preparing for coding interviews
• Software engineers
• Programmers
• Competitive programmers

An effective algorithmic technique used in computer programming is called dynamic programming, and it is used to solve a class of problems with overlapping subproblems and optimal substructure properties. Any problem's solutions can be kept for later use if they can be broken down into smaller subproblems, which can then be broken down into even smaller subproblems, and if there is overlap between the subproblems. In this approach, utilising dynamic programming, algorithms can be enhanced and many issues can be optimised. One of the most significant and potent algorithmic strategies that can be used to tackle a variety of computational problems is dynamic programming. It's an essential skill to acquire to improve your algorithmic and problem-solving abilities. But many students struggle to comprehend dynamic programming and use it to solve issues; if this describes you, then this course is perfect for you!