Implementing dynamic programming algorithms is more of an art than just a programming technique. Dynamic programming problems are also very commonly asked in coding interviews but if you ask anyone who is preparing for coding interviews which are the toughest problems asked in interviews most likely the answer is going to be dynamic programming.

In fact, dynamic programming problems are very easy to solve once you understand the theory in depth and know certain tricks. Most of the dynamic programming problems share some common elements and if you know how to identify those things you can come up with solutions easily.

In this course, you will learn about N number of questionssuch as 0/1 KNAPSACK , MinCostPATH, LCS, Edit DISTANCE ETC.

In this course, you will learn about:

1. The in-depth theory behind dynamic programming

2. How to derive Recursive formulas for DP.

3. All videos have codes and every line will be typed infront of you to make you Understand Properly.

4. Applying step by step approach for one-dimensional dynamic programming problems with detailed examples

5. Applying step by step approach for multi dimensional dynamic programming problems with detailed examples

Who this course is for:

• This course is meant for newbies who are not familiar with algorithmic problems in the main or students looking for some refresher

• Anyone preparing for programming interviews or interested in improving their problem solving skills

• Computer Science Students

• Programmers and Coders

• Students preparing for coding interviews

• Software engineers