Dynamic Programming Playlist | Coding | Interview Questions | Tutorials | Algorithm
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What you'll learn
This course includes
- 16 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 49 lessons • 16 hours of video
Dynamic Programming Playlist | Coding | Interview Questions | Tutorials | Algorithm
49 lessons
• 16 hours
Dynamic Programming Playlist | Coding | Interview Questions | Tutorials | Algorithm
49 lessons
• 16 hours
- Dynamic Programming | Introduction 13:57
- 2 Types of knapsack 13:50
- 3 01 Knapsack Recursive 21:04
- 4 01Knapsack Memoization 13:53
- 5 01 Knapsack Top Down DP 41:08
- 6 Identification of Knapsack Problems and Introduction 06:18
- 7 Subset Sum Problem 27:13
- Equal Sum Partition Problem 18:01
- 9 Count of Subsets Sum with a Given Sum 20:49
- 10 Minimum Subset Sum Difference 46:41
- 11 Count the number of subset with a given difference 16:52
- 12 Target sum 08:39
- 13 Unbounded Knapsack 16:59
- 14 Rod Cutting Problem 18:53
- 15 Coin change problem: Maximum number of ways 21:16
- 16 Coin change problem: Minimum number of coins 25:54
- 17 Coin change problem Contd. 00:50
- 18 Longest common subsequence Introduction 05:08
- 19 Longest common subsequence Recursive 27:42
- 20 Longest common subsequence Memoization 31:19
- 21 Longest common subsequence Top down DP 25:35
- 22 Longest Common Substring 13:00
- 23 Printing Longest common subsequence 26:45
- 24 Shortest Common SuperSequence 22:59
- 25 Minimum Number of Insertion and Deletion to convert String a to String b 15:02
- 26 Longest Palindromic Subsequence 12:46
- 28 Minimum number of deletion in a string to make it a palindrome 11:44
- 29 Print shortest common Supersequence 23:09
- 30 Longest repeating subsequence 12:58
- 31 Sequence Pattern Matching 10:26
- 32 Minimum number of insertion in a string to make it a palindrome 13:13
- 33 Matrix chain multiplication Introduction Identification and General Format 22:10
- 34 Matrix Chain Multiplication Recursive 40:47
- 35 Matrix chain multiplication Memoization 16:29
- 36 Palindrome Partitioning Recursive 26:35
- 37 Palindrome Partitioning Memoization 18:54
- 38 Palindrome Partitioning Memoized Optimisation 10:16
- 39 Evaluate Expression to True Boolean Parenthesization Recursive 40:00
- 40 Evaluate Expression To True Boolean Parenthesization Memoized 28:12
- 41 Scrambled String Recursive 45:48
- 42 Scrambled String Memoized 19:27
- 43 Egg Dropping Problem Recursive 30:10
- 44 Egg Dropping Problem Memoization 15:43
- 45 Egg Dropping Problem Memoization Optimization 07:58
- 46 Dynamic programming on Trees Introduction and Identification 08:33
- 47 Dynamic Programming on Tree General Syntax 15:41
- 48 Diameter of a Binary Tree 15:13
- 49 Maximum Path Sum | From any node to any node 12:16
- 50 Maximum Path sum | From leaf node to leaf node 11:35
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