Dynamic programming

Dynamic programming is one of the most important and powerful algorithmic techniques that can be used to solve a lot of computational problems, it’s a fundamental technique to learn to strengthen your algorithms and problem solving skills

But, a lot of students find hard times understanding dynamic programming and being able to apply it to solve problems, if you are in this situation, this course is made for you!

Why you should take this course:

Covers all what you need to know to start using dynamic programming to solve problems (introduction, recursion, how to recognize a dynamic programming problem, memoization, tabulation…)

Shows you a technique to solve almost any dynamic programming problem

Has an active instructor that is ready to answer to your questions and doubts in case you don’t understand something

Explains the time and space complexity analysis of each solved problem

Includes 20 different interesting dynamic programming problems to practice on with the ability to test your Python solution on different test cases before watching the solution

Practice problems are:

Paths in matrix

House robber

Longest common subsequence

Gold mine

Edit distance

Ways to climb

Shortest common supersequence

Coin change

0–1 Knapsack

Subset sum

Longest increasing subsequence