Dynamic programming

About Dynamic programming

WARNING: The instructor is not currently available to answer questions regarding this course 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!