Dynamic Programming Algorithms for Coding Interview
Mastering Dynamic Programming: Your Path to Effortless Problem Solving in Coding Interviews
Updated on Apr, 2024
Language - English
Development,Programming Languages
Lectures -88
Duration -30 hours
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Course Description
Are you ready to conquer dynamic programming and stand out in coding interviews? This comprehensive course is designed to equip you with the skills and strategies needed to excel in solving dynamic programming problems during technical interviews.
Dynamic programming is a fundamental technique that separates average coders from exceptional problem solvers. In this course, you'll delve into the world of dynamic programming algorithms, unraveling complex problems by breaking them down into manageable subproblems and optimizing solutions through reusability.
Course Highlights:
Foundation Building: Understand the core concepts of dynamic programming, learning to identify problems that can be solved using this technique and grasp the underlying principles.
Problem Classification: Explore a wide range of classic dynamic programming problems, including Fibonacci sequence, longest common subsequence, knapsack, coin change, and more. Learn to classify problems based on their characteristics for effective problem-solving strategies.
Optimization Strategies: Dive into the art of optimizing solutions, discovering techniques such as memoization and tabulation. Uncover the pros and cons of each approach and determine when to use them.
Step-by-Step Guidance: Through hands-on examples and walkthroughs, learn how to apply dynamic programming to various problem scenarios. Follow step-by-step explanations to transform complex problems into simple subproblems.
Real-World Applications: Explore how dynamic programming is used in real-world scenarios, such as optimizing resource allocation, efficient sequence alignment, and network routing.
Problem Solving Framework: Develop a systematic problem-solving framework for dynamic programming, encompassing problem understanding, recurrence formulation, base case identification, and solution construction.
Algorithmic Insight: Gain a deeper understanding of algorithmic strategies by analyzing time and space complexities. Learn to strike the right balance between efficiency and simplicity.
Interview-Ready Practice: Acquire practical experience by solving a variety of dynamic programming problems similar to those encountered in coding interviews. Strengthen your ability to communicate your thought process and solutions effectively.
Case Studies: Study real coding interview scenarios where dynamic programming shines. Examine successful approaches to tackle challenging questions posed by top tech companies.
Lifetime Skills: Beyond interviews, the problem-solving skills you'll acquire in this course will serve you in competitive programming, software development, and any context that demands efficient algorithmic thinking.
Embark on this journey to master dynamic programming and elevate your coding interview performance. Whether you're a beginner seeking to understand the fundamentals or an experienced programmer aiming to refine your techniques, this course will equip you with the tools to confidently tackle dynamic programming problems and emerge victorious in coding interviews. Enroll now and transform complex problems into your stepping stones to success!
Goals
What will you learn in this course:
- Unravel the art of dynamic programming and amplify your coding interview prowess with our comprehensive course. Dive into the world of algorithmic problem solving, where complex challenges are dissected into solvable components using dynamic programming techniques. From classic conundrums like Fibonacci sequences and knapsack problems to advanced conceptions like longest common subsequences and optimal matrix multiplication, this course empowers you to demystify problems, optimize solutions, and emerge as a dynamic programming virtuoso. Elevate your problem-solving capabilities, master the strategies, and set your trajectory towards interview success.
Prerequisites
What are the prerequisites for this course?
- Basic programming skills in a language of your choice (e.g., Python, Java) and familiarity with elementary algorithms and data structures.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
1 Lectures
-
Introduction
00:42
00:42
0/1 Knapsack
3 Lectures
Target Sum
2 Lectures
Count of Subset Sum
3 Lectures
Minimum Sum Partition
2 Lectures
Minimum Number of Refueling Stops
2 Lectures
Partition Equal Subset Sum
2 Lectures
Count Square Submatrices with All Ones
2 Lectures
Unbounded Knapsack
3 Lectures
Maximum Ribbon Cut
2 Lectures
Rod Cutting
2 Lectures
Coin Change
2 Lectures
Coin Change II
3 Lectures
Fibonacci Number
3 Lectures
Climbing Stairs
2 Lectures
Decode Ways
3 Lectures
House Robber
2 Lectures
Number Factor
2 Lectures
Count Ways to Score in a Game
2 Lectures
Unique Paths to Goal
2 Lectures
Nth Tribonacci Number
2 Lectures
The Catalan Numbers
2 Lectures
Minimum jumps to reach the End
2 Lectures
Minimum Jumps with fee
2 Lectures
Matrix Chain Multiplication
2 Lectures
Longest Common Substring
2 Lectures
Long Common Subsequence
2 Lectures
Shortest Common Supersequence
2 Lectures
Minimum Number of Deletions and Insertions
2 Lectures
Edit Distance
2 Lectures
Longest Repeating Subsequence
2 Lectures
Distinct Subsequence Pattern Matching
2 Lectures
Interleaving String
2 Lectures
Longest Increasing Subsequence
2 Lectures
Number of Longest Increasing Subsequence
1 Lectures
Minimum Deletions to Make a String Stored
2 Lectures
Longest Bitonic Subsequence
1 Lectures
Longest Alternating Subsequence
1 Lectures
Building Bridges
1 Lectures
Longest Palindromic Subsequence
2 Lectures
Minimum Deletions to Make a String Palindrome
2 Lectures
Longest Palindromic Substring
2 Lectures
Count ogf Palindromic Substrings
2 Lectures
Palindrome Partitioning
2 Lectures
Instructor Details
Md A Barik
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