Dynamic Programming 6-step Framework Part II

Dynamic Programming 6-step Framework Part II
Compiled list of Dynamic Programming Leetcode questions to Ace your Next Interview

What you will learn

6 Step Dynamic Programming Framework to solve any DP problem

Gradually build from recursive (top down) approach to tabulation (bottom up)

Enhance problem-solving skills by tackling a diverse range of dynamic programming problems

Prepare for coding interviews, particularly those conducted by leading tech companies


Embark on a journey into one of the most renowned and challenging realms of programming with our dynamic programming course. Despite its reputation for complexity, we are dedicated to demystifying dynamic programming, delving deep into its foundational principles.

The course commences by introducing and defining dynamic programming, unveiling two widely utilized techniques: memoization and tabulation. We thoroughly explore their distinctions, guiding you on when and where to deploy each method effectively.

Moving beyond theory, we tackle renowned dynamic programming problems, providing detailed problem statements and conducting illustrative walkthroughs. Notably, dynamic programming plays a significant role in tech giant interviews, and our course meticulously compiles essential problems crucial for establishing a robust DP foundation. We will learn how top apply 6 step DP framework to solve any DP problem:

1. Category

2. States

3. Decisions


4. Base Case

5. Code

6. Optimize (Time or Space Complexity)

We will solve problems from 5 different categories:

  1. 0/1 Knapsack
  2. Unbounded Knapsack
  3. Shortest/Critical Path
  4. Fibonacci Sequence
  5. Longest Common Substring/Subsequence

This will be series of free course exploring different problems from DP Leetcode Category. Every students that joins is free to use our platform containing 200 problems in 4 different programming languages split by company/category with deep dive videos. Link for it can be found as external resource inside each lecture.

Problem Set

Best Time to Buy and Sell Stock with Cooldown
Unique Paths
Longest Increasing Subsequence
Longest Palindromic Substring
Palindromic Substrings
Maximal Square
Target Sum
Partition Equal Subset Sum
Word Break

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