Grokking Dynamic Programming Patterns for Coding Interviews

Description

In this course, you will learn :

• Simple techniques for dealing with any DP issue. Instead of simply trying to memorise solutions, you'll be guided through five underlying DP patterns that can then be applied to 35+ DP problems.
• A recursive brute-force solution – this is the best way to begin solving a DP problem!
• Use the advanced DP methods of Memoization and Tabulation once we've found a recursive solution.

Syllabus :

1. 0/1 Knapsack

• 0/1 Knapsack
• Equal Subset Sum Partition
• Subset Sum
• Minimum Subset Sum Difference
• Count of Subset Sum
• Target Sum

 

2. Unbounded Knapsack

• Unbounded Knapsack
• Rod Cutting
• Coin Change
• Minimum Coin Change
• Maximum Ribbon Cut

 

3.  Fibonacci Numbers

• Fibonacci numbers
• Staircase
• Number factors
• Minimum jumps to reach the end
• Minimum jumps with fee
• House thief

 

4.  Palindromic Subsequence

• Longest Palindromic Subsequence
• Longest Palindromic Substring
• Count of Palindromic Substrings
• Minimum Deletions in a String to make it a Palindrome
• Palindromic Partitioning

 

5.  Longest Common Substring

• Longest Common Substring
• Longest Common Subsequence
• Minimum Deletions & Insertions to Transform a String into another
• Longest Increasing Subsequence
• Maximum Sum Increasing Subsequence
• Shortest Common Super-sequence
• Minimum Deletions to Make a Sequence Sorted
• Longest Repeating Subsequence
• Subsequence Pattern Matching
• Longest Bitonic Subsequence
• Longest Alternating Subsequence
• Edit Distance
• Strings Interleaving

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