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:

1. Paths in matrix

2. House robber

3. Longest common subsequence

4. Gold mine

5. Edit distance

6. Ways to climb

7. Shortest common supersequence

8. Coin change

9. 0-1 Knapsack

10. Subset sum

11. Longest increasing subsequence

12. Ways to decode

13. Rod cutting

14. Interleaving string

15. Square matrix of ones

16. Partition problem

17. Sorted vowel strings

18. Minimum cost for tickets

19. Word break

20. Matrix chain multiplication

If you have any other question concerning this course that you want to ask before enrolling, you can send me a message on Instagram at @inside.code

Enjoy!