Grokking Dynamic Programming Patterns for Coding Interviews
Master Dynamic Programming by learning coding patterns. Act smartly, and follow the Dynamic Programming patterns.
Level:
Advanced
Study Time:
71h
Chapters:
73
Playgrounds :
142
39,106 (Students)
Course Overview
The fact is, Dynamic Programming (DP) problems can be some of the most intimidating on a coding interview. Even when it's actually clear if a problem can be solved using DP (which it rarely is), it can be pretty challenging to even know where to start on the solution. Unless, that is, you're trained on the approach to solving DP problems.
This course was made from scratch with just that goal in mind. It'll equip you with a set of easy-to-understand techniques to handle any DP problem. Rather than just having you try to memorize solutions, you'll be walked through five underlying DP patterns that can then be applied to solve 35+ DP problems. In each pattern, we'll start with a recursive brute-force solution -- this is actually the best way to start solving a DP problem! Once we have a recursive solution, we'll then apply the advanced DP methods of Memoization and Tabulation.
The practice problems in this course were carefully chosen, covering the most frequently asked DP questions in coding interviews.
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Course Content
• 7 Chapters • 73 Lessons
1.
Introduction
1 chapter
What is Dynamic Programming?
2.
Pattern 1: 0/1 Knapsack
13 chapters
Introduction
0/1 Knapsack
Solution: 0/1 Knapsack
Equal Subset Sum Partition
Solution: Equal Subset Sum Partition
Subset Sum
Solution: Subset Sum
Minimum Subset Sum Difference
Solution: Minimum Subset Sum Difference
Count of Subset Sum
Solution: Count of Subset Sum
Target Sum
Solution: Target Sum
3.
Pattern 2: Unbounded Knapsack
10 chapters
Unbounded Knapsack
Solution: Unbounded Knapsack
Rod Cutting
Solution: Rod Cutting
Coin Change
Solution: Coin Change
Minimum Coin Change
Solution: Minimum Coin Change
Maximum Ribbon Cut
Solution: Maximum Ribbon Cut
4.
Pattern 3: Fibonacci Numbers
12 chapters
Fibonacci numbers
Solution: Fibonacci numbers
Staircase
Solution: Staircase
Number factors
Solution: Number factors
Minimum jumps to reach the end
Solution: Minimum jumps to reach the end
Minimum jumps with fee
Solution: Minimum jumps with fee
House thief
Solution: House thief
5.
Pattern 4: Palindromic Subsequence
10 chapters
Longest Palindromic Subsequence
Solution: Longest Palindromic Subsequence
Longest Palindromic Substring
Solution: Longest Palindromic Substring
Count of Palindromic Substrings
Solution: Count of Palindromic Substrings
Minimum Deletions in a String to make it a Palindrome
Solution: Minimum Deletions in a String to make it a Palindrome
Palindromic Partitioning
Solution: Palindromic Partitioning
6.
Pattern 5: Longest Common Substring
26 chapters
Longest Common Substring
Solution: Longest Common Substring
Longest Common Subsequence
Solution: Longest Common Subsequence
Minimum Deletions & Insertions to Transform a String into another
Solution: Minimum Deletions & Insertions to Transform a String into another
Longest Increasing Subsequence
Solution: Longest Increasing Subsequence
Maximum Sum Increasing Subsequence
Solution: Maximum Sum Increasing Subsequence
Shortest Common Super-sequence
Solution: Shortest Common Super-sequence
Minimum Deletions to Make a Sequence Sorted
Solution: Minimum Deletions to Make a Sequence Sorted
Longest Repeating Subsequence
Solution: Longest Repeating Subsequence
Subsequence Pattern Matching
Solution: Subsequence Pattern Matching
Longest Bitonic Subsequence
Solution: Longest Bitonic Subsequence
Longest Alternating Subsequence
Solution: Longest Alternating Subsequence
Edit Distance
Solution: Edit Distance
Strings Interleaving
Solution: Strings Interleaving
7.
Appendix
1 chapter
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