What you'll learn

Importance of dynamic programming

How to use the top-down approach of dynamic programming (memoization)

How to use the bottom-up approach of dynamic programming (tabulation)

How to solve almost any dynamic programming problem

Description

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

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 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 (video coming soon)

Coin change

0-1 Knapsack

Subset sum (video coming soon)

Longest increasing subsequence

Ways to decode (video coming soon)

Rod cutting (video coming soon)

Interleaving string (video coming soon)

Square matrix of ones (video coming soon)

Partition problem (video coming soon)

Sorted vowel strings (video coming soon)

Minimum cost for tickets (video coming soon)

Word break (video coming soon)

Matrix chain multiplication (video coming soon)

Who this course is for:

Computer science students

Software eeering students

Programmers

Competitive programmers




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