Grokking Dynamic Programming Patterns: Coding Interviews

32h 34m 13s
English
Paid

Course description

This course on Dynamic Programming Coding Interview Algorithms will teach you the advanced algorithms and data structures needed for coding interviews and technical interviews. You’ll learn how to solve dynamic programming questions, and you’ll master the fundamentals of data structures and algorithms. You’ll also get an in-depth understanding of Grokking Dynamic Programming Interview Patterns for Technical Interviews, and you’ll learn the skills needed to solve the toughest coding interview questions. Finally, you’ll get hands-on experience with Java Dynamic Programming questions and Algorithms for Coding Interviews, and you’ll Master Dynamic Programming Coding Interview Algorithms and ace your next job interview. This course will teach you the fundamentals of dynamic programming and how to use them to solve complex coding interview questions quickly and confidently. You will learn the fundamentals of data structures and algorithms, as well as how to apply them to coding interview questions. You will also learn to use Java and dynamic programming techniques to solve dynamic programming questions related to Google, LeetCode, and other technical interviews. You will also learn the best practices for mastering the coding interview data structures and algorithms, as well as how to review and apply them in the real world.

Read more about the course

If you often struggle with dynamic programming problems despite your understanding of data structures and algorithms, this course is designed to bridge that gap. It provides a comprehensive understanding of critical Dynamic Programming concepts, empowering you to excel in competitive coding and interviews.

In addition to the mentioned problems, the "Dynamic Programming Algorithms Coding Interviews" course covers several more essential dynamic programming problems. Through detailed explanations, code implementations, and step-by-step walkthroughs, you'll gain a deep understanding of each problem's solution.

Watch Online

This is a demo lesson (10:00 remaining)

You can watch up to 10 minutes for free. Subscribe to unlock all 96 lessons in this course and access 10,000+ hours of premium content across all courses.

View Pricing

Watch Online Grokking Dynamic Programming Patterns: Coding Interviews

0:00
/
#1: Introduction

All Course Lessons (96)

#Lesson TitleDurationAccess
1
Introduction Demo
00:43
2
0/1 Knapsack Problem - Top Down
24:52
3
0/1 Knapsack Problem - Bottom UP (2D Tabulation)
24:28
4
0/1 Knapsack Problem - Bottom UP (1D Tabulation)
21:28
5
Target Sum - Top Down
29:14
6
Target Sum - Bottom UP
47:43
7
Count of Subset Sum - Top Down
32:54
8
Count of Subset Sum - Bottom Up [2D Tabulation]
20:53
9
Count of Subset Sum - Bottom UP [1D Tabulation]
26:53
10
Minimum Sum Partition - Top Down
28:32
11
Minimum Sum Partition - Bottom UP [1D Tabulation]
20:24
12
Minimum Number of Refuelling Stops - Top Down
33:39
13
Minimum Number of Refuelling Stops - Bottom UP [1D Tabulation]
25:28
14
Partition Equal Subset Sum - Top Down
20:41
15
Partition Equal Subset Sum - Bottom UP [1D Tabulation]
20:03
16
Count Square Submatrices with All Ones - Top Down
23:46
17
Count Square Submatrices with All Ones - Bottom Up
16:31
18
Unbounded Knapsack - Top Down
27:33
19
Unbounded Knapsack - Bottom UP [2D Tabulation]
17:35
20
Unbounded Knapsack - Bottom UP [1D Tabulation]
13:03
21
Maximum Ribbon Cut - Top Down
17:48
22
Maximum Ribbon Cut - Bottom UP [2D Tabulation]
18:13
23
Rod Cutting - Top Down
20:09
24
Rod Cutting - Bottom UP [2D Tabulation]
15:57
25
Coin Change - Top down
15:42
26
Coin Change - Bottom UP [1D Tabulation]
28:44
27
Coin Change II - Top Down
17:04
28
Coin Change II - Bottom UP [2D Tabulation]
15:14
29
Coin Change II - Bottom UP [1D Tabulation]
15:45
30
Fibonacci Number - Top Down
24:25
31
Fibonacci Number - Bottom UP [1D Tabulation]
08:52
32
Fibonacci Number - Bottom UP [Constant Space]
08:47
33
Climbing Stairs - Top Down
16:22
34
Climbing Stairs - Bottom UP
22:21
35
Decode Ways - Top Down
24:42
36
Decode Ways - Bottom UP [1D Tabulation]
28:58
37
Decode Ways - Bottom UP [Space Optimized]
17:51
38
House Robber - Top Down
17:51
39
House Robber - Bottom UP
20:47
40
Number Factors - Top Down
15:57
41
Number Factors - Bottom UP
10:42
42
Count Ways to Score in a Game - Top Down
16:37
43
Count Ways to Score in a Game - Bottom UP
08:01
44
Unique Paths to Goal - Top Down
19:48
45
Unique Paths to Goal - Bottom UP
18:01
46
Nth Tribonacci Number - Top Down
20:11
47
Nth Tribonacci Number - Bottom UP
12:35
48
The Catalan Numbers - Top Down
22:17
49
The Catalan Numbers - Bottom UP
12:04
50
Minimum Jumps to Reach the End - Top Down
15:56
51
Minimum Jumps to Reach the End - Bottom UP
13:44
52
Minimum Jumps With Fee - Top Down
23:31
53
Minimum Jumps With Fee - Bottom UP
17:50
54
Matrix Chain Multiplication - Top Down
42:05
55
Matrix Chain Multiplication - Bottom UP
31:38
56
Longest Common Substring - Top Down
22:30
57
Longest Common Substring - Bottom UP
13:29
58
Longest Common Subsequence - Top Down
22:53
59
Longest Common Subsequence - Bottom UP [2D Tabulation]
17:25
60
Shortest Common Supersequence - Top Down
21:14
61
Shortest Common Supersequence - Bottom UP
19:20
62
Minimum Number of Deletions and Insertions - Top Down
27:33
63
Minimum Number of Deletions and Insertions - Bottom UP
15:10
64
Edit Distance -- Top Down
35:08
65
Edit Distance -- Bottom UP [2D Tabulation]
27:55
66
Longest Repeating Subsequence - Top Down
21:47
67
Longest Repeating Subsequence - Bottom UP
09:11
68
Distinct Subsequence Pattern Matching - Top Down
15:39
69
Distinct Subsequence Pattern Matching - Bottom UP
14:22
70
Interleaving String - Top Down
27:50
71
Interleaving String - Bottom UP
19:29
72
Word Break - Bottom UP [1D Tabulation]
16:24
73
Word Break II - Top Down
21:02
74
Word Break II - Bottom UP
17:26
75
Longest Increasing Subsequence - Top Down
20:06
76
Longest Increasing Subsequence - Bottom UP [1D Tabulation]
25:00
77
Number of Longest Increasing Subsequence - Bottom UP
19:52
78
Minimum Deletions to Make a String Sorted - Top Down
18:37
79
Minimum Deletions to Make a String Sorted - Bottom UP
16:46
80
Maximum Sum Increasing Subsequence - Top Down
16:01
81
Maximum Sum Increasing Subsequence - Bottom UP
07:34
82
Longest Bitonic Subsequence - Bottom UP
20:07
83
Longest Alternating Subsequence - Bottom UP
13:27
84
Building Bridges - Bottom UP
22:46
85
Solution (i): Longest Palindromic Subsequence - Top Down
22:14
86
Solution (ii): Longest Palindromic Subsequence - Bottom UP [2D Tabulation]
23:17
87
Minimum Deletions to Make a String Palindrome - Top Down
15:18
88
Minimum Deletions to Make a String Palindrome - Bottom UP [2D]
13:42
89
Longest Palindromic Substring - Top Down
22:52
90
Longest Palindromic Substring - Bottom UP
21:25
91
Count of Palindromic Substrings - Top Down
28:04
92
Count of Palindromic Substrings - Bottom UP
15:37
93
Palindrome Partitioning - Top Down
19:27
94
Palindrome Partitioning - Bottom UP
24:41
95
Regular Expression Matching [2D Tabulation]
32:47
96
Range Sum Query 2D - Immutable [2D Tabulation]
15:54

Unlock unlimited learning

Get instant access to all 95 lessons in this course, plus thousands of other premium courses. One subscription, unlimited knowledge.

Learn more about subscription

Comments

0 comments

Want to join the conversation?

Sign in to comment

Similar courses

Java Puzzles to Eliminate Code Fear

Java Puzzles to Eliminate Code Fear

Sources: udemy
The motivation behind this course came from an article titled "Why Can't Programmers Program?" by Jeff Atwood. It talks about how poorly many candidates perform
7 hours 33 minutes 44 seconds
Python Interview Espresso

Python Interview Espresso

Sources: interviewespresso (Aaron Jack)
Learn the algorithms, patterns, and process in Python.
5 hours 11 minutes 29 seconds
Ace Your Tech Interview And Get A Job As A Software Engineer

Ace Your Tech Interview And Get A Job As A Software Engineer

Sources: Alex Chiou
Finding a job as a software engineer is difficult. From tricky tasks on data structures and algorithms (DSA) to recruiters who simply stop responding...
4 hours 38 minutes 35 seconds
JavaScript Interview Espresso

JavaScript Interview Espresso

Sources: interviewespresso (Aaron Jack)
Learn the algorithms, patterns, and process in JavaScript.
5 hours 11 minutes 16 seconds