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Intermediate
25h
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Grokking Dynamic Programming Interview Save
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The ultimate guide to dynamic programming interviews. Developed by FAANG engineers, it equips you with strategic DP skills, practice with real-world questions, and patterns for efficient solutions.
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Some of the toughest questions in technical interviews require dynamic programming solutions. Dynamic programming (DP) is an advanced optimization technique applied to recursive solutions. However, DP is not a one-size-fits-all technique, and it requires practice to develop the ability to identify the underlying DP patterns. With a strategic approach, coding interview prep for DP problems shouldn’t take more than a few weeks.
This course starts with an introduction to DP and thoroughly discusses five DP patterns. You’ll learn to apply each pattern to several related problems, with a visual representation of the working of the pattern, and learn to appreciate the advantages of DP solutions over naive solutions.
After completing this course, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence.
This course is also available in C++, JavaScript, and Python—with more coming soon!
Some of the toughest questions in technical interviews require dynamic programming solutions. Dynamic programming (DP) is an adv...Show More
WHAT YOU'LL LEARN
A deep understanding of the essential patterns behind common dynamic programming interview questions—without having to drill endless problem sets
The ability to identify and apply the underlying pattern in an interview question by assessing the problem statement
Familiarity with dynamic programming techniques with hands-on practice in a setup-free coding environment
The ability to efficiently evaluate the tradeoffs between time and space complexity in different solutions
A flexible conceptual framework for solving any dynamic programming question, by connecting problem characteristics and possible solution techniques
A deep understanding of the essential patterns behind common dynamic programming interview questions—without having to drill endless problem sets
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Content
1.
Getting Started
3 Lessons
Learn how to use dynamic programming to solve optimization problems efficiently for coding interviews.
2.
0/1 Knapsack
9 Lessons
Grasp the fundamentals of solving optimization problems using dynamic programming techniques.
3.
Unbounded Knapsack
6 Lessons
Go hands-on with optimizing recursive problems using dynamic programming for maximum efficiency.
4.
Recursive Numbers
12 Lessons
Grasp the fundamentals of recursive algorithms and optimize with dynamic programming.
5.
Longest Common Substring
16 Lessons
Deepen your knowledge of finding common, repeating, and interleaving substrings using dynamic programming.
Introduction to Longest Common SubstringSolving the Longest Common Substring ProblemLongest Common SubsequenceShortest Common SupersequenceMinimum Number of Deletions and InsertionsEdit Distance ProblemLongest Repeating SubsequenceDistinct Subsequence Pattern MatchingInterleaving StringsWord Break IILongest Increasing SubsequenceMinimum Deletions to Make a Sequence SortedMaximum Sum Increasing SubsequenceLongest Bitonic SubsequenceLongest Alternating SubsequenceBuilding Bridges
6.
Palindromic Subsequence
6 Lessons
See how it works to identify palindromic subsequences, substrings, and efficient partitioning methods.
7.
Conclusion
1 Lessons
Piece together the parts of your learning journey and continue improving your skills.
Certificate of Completion
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Developed by MAANG Engineers
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Frequently Asked Questions
What is the difference between memoization and tabulation in dynamic programming?
How can I practice dynamic programming to improve interviews?
How can I recognize if a problem is suited for dynamic programming?
Why is dynamic programming emphasized in technical interviews?
