Lecture 8 : Dynamic Programming in Shot of Competitive Programming | Competitive Programming скачать в хорошем качестве

Lecture 8 : Dynamic Programming in Shot of Competitive Programming | Competitive Programming

In Lecture 8 of the Competitive Programming series, we dive deep into Dynamic Programming (DP), one of the most powerful techniques used to solve complex problems efficiently. DP helps in breaking down problems into smaller overlapping subproblems, optimizing solutions that would otherwise take too much time to compute. Whether you're tackling knapsack problems, longest common subsequence, or Fibonacci sequences, mastering DP will greatly improve your problem-solving skills in competitive programming. You'll learn key DP concepts, such as memoization, tabulation, and how to identify when DP is the right approach. By the end of this lecture, you’ll be equipped with the skills to tackle tough problems that require optimization and time-efficient solutions. Lecture Timestamps:- 00:00:00 Introduction 00:01:49 What is Dynamic Programming? 00:07:30 Agenda for this video 00:11:03 Introduction to DP 00:26:02 Top Down Approach or Memoization 00:42:50 Bottom Up Approach or Tabulation 00:57:00 Fibonaccharsis 01:21:50 Knapsack Problem 01:50:28 Take or Not Take Concept 01:51:22 Subset Sum Problem 02:08:31 House Robber Problem 02:29:40 Frog Jump Problem 02:52:20 DP with Matrix 03:08:08 Longest Common Subsequence 03:28:58 Longest Increasing Subsequence using DP 03:39:00 Longest Increasing Subsequence using Binary Search 03:46:08 Conclusion00:00:00 Introduction 00:01:49 What is Dynamic Programming? 00:07:30 Agenda for this video 00:11:03 Introduction to DP 00:26:02 Top Down Approach or Memoization 00:42:50 Bottom Up Approach or Tabulation 00:57:00 Fibonaccharsis 01:21:50 Knapsack Problem 01:50:28 Take or Not Take Concept 01:51:22 Subset Sum Problem 02:08:31 House Robber Problem 02:29:40 Frog Jump Problem 02:52:20 DP with Matrix 03:08:08 Longest Common Subsequence 03:28:58 Longest Increasing Subsequence using DP 03:39:00 Longest Increasing Subsequence using Binary Search 03:46:08 Conclusion Here are the problems solved in the class: ➡️https://cp-algorithms.com/dynamic_pro... ➡️https://leetcode.com/problems/fibonac... ➡️https://leetcode.com/problems/climbin... ➡️https://codeforces.com/contest/1853/s... ➡️https://atcoder.jp/contests/dp/submis... ➡️https://leetcode.com/problems/partiti... ➡️https://leetcode.com/problems/house-r... ➡️https://atcoder.jp/contests/dp/submis... ➡️https://atcoder.jp/contests/dp/submis... ➡️https://leetcode.com/problems/longest... ➡️https://atcoder.jp/contests/dp/tasks/... ➡️https://leetcode.com/problems/longest... ➡️https://leetcode.com/problems/longest... 📌Book your 1:1 career counselling session with our Experts, Fill the form Now-https://forms.gle/iaaC4EkRw52x9BXY9 Start Your Upskilling Journey #vishwasdiwaswithpw 📌Decode DSA Batches-https://pwskills.com/category/program... 📌Decode C++ with DSA-https://pwskills.com/course/dsa-cpp/?... 📌Decode Python with DSA-https://pwskills.com/course/dsa-in-py... 📌Decode Java with DSA-https://pwskills.com/course/decode-ja... 📌Decode Programming Powerhouse: C++, Java, Python & DSA Course-https://pwskills.com/course/decode-pr... 📌Data Analytics Course-https://pwskills.com/course/data-anal... 📌Full Stack Development Course-https://pwskills.com/course/full-stac... 📌Data Science with Generative AI Course-https://pwskills.com/course/data-scie... 📌DevOps and Cloud Computing Course-https://pwskills.com/course/devops-an... 📌UI/UX Design Course-https://pwskills.com/course/ui-ux-des... Lecture 8 : Dynamic Programming in Shot of Competitive Programming | Competitive Programming #DynamicProgramming #CompetitiveProgramming #DP #AlgorithmDesign #ProblemSolving #KnapsackProblem #Fibonacci #CodeOptimization #TechSkills #ProgrammingLanguages #CompetitiveCoder #LearnToCode #EfficientCoding