Data Structures and Algorithms with Python | Free DSA with Python Course

๐Ÿš€ Welcome to the Free DSA with Python Course Playlist by Code & Debug! This comprehensive playlist is designed to help you master Data Structures and Algorithms (DSA) using Python, one of the most versatile programming languages. Whether youโ€™re a beginner or preparing for coding interviews, this course is your one-stop solution to understanding and implementing DSA concepts effectively. ๐ŸŽฏ What youโ€™ll learn in this playlist: โœ… Arrays, Linked Lists, Stacks, Queues, and Hashing โœ… Sorting Algorithms like Quick Sort, Merge Sort, and Bubble Sort โœ… Searching Techniques including Linear Search and Binary Search โœ… Advanced topics like Recursion, Dynamic Programming, and Graph Algorithms โœ… Real-world coding problems from Leetcode and other platforms ๐Ÿ’ก Key features of this course: ๐Ÿ“Œ Beginner-friendly explanations ๐Ÿ“Œ Practical Python implementations ๐Ÿ“Œ Real coding interview questions ๐Ÿ“Œ Step-by-step problem-solving approach ๐Ÿ‘‰ Start learning for free today and level up your coding game! ๐Ÿ™ Donโ€™t forget to subscribe to Code & Debug and hit the ๐Ÿ”” for notifications about our upcoming videos. Letโ€™s make DSA with Python simple and fun together! #DSAWithPython #PythonDSA #DataStructuresAndAlgorithms #CodeAndDebug #FreeDSACourse #LearnPython #CodingInterviews

Curated by: Code and Debug (230 videos)


Currently Playing: DSA in Python - Advanced Recursion | Count All Subsequences with Sum K | Backtracking - Part 72

๐Ÿš€ Welcome to Part 72 of Code & Debugโ€™s DSA in Python Course! In this lecture, we extend our Advanced Recursion concepts by solving Count All Subsequences with Sum K using Recursion & Backtracking. This is a critical problem in Dynamic Programming, Combinatorics, and Optimization Problems. ๐Ÿ“š What youโ€™ll learn in this video: โœ… Understanding the problem statement & constraints โœ… Recursive approach to count valid subsequences โœ… Optimizing using Backtracking to reduce redundant computations โœ… Time complexity analysis of the recursive approach โœ… Handling edge cases efficiently ๐Ÿ’ก Why is this important? This problem is fundamental for Subset Sum Problems, Combinatorial Counting, and Dynamic Programming. It is frequently asked in FAANG interviews and helps in efficiently solving counting-based problems using recursion and backtracking. ๐Ÿ‘‰ Link to solve this question: https://www.geeksforgeeks.org/problems/perfect-sum-problem5633/1 ๐Ÿ‘‰ Refer the article below for better understanding: https://codeanddebug.in/blog/count-all-subsequences-with-sum-k/ ๐Ÿ‘‰ ๐Ÿ“„ Access the full YouTube DSA Playlist Sheet (All Questions in Order): ๐Ÿ”— https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing ๐Ÿ‘‰ Enroll in the free DSA Python course here: https://codeanddebug.in/course/master-dsa-with-leetcode ๐Ÿ‘‰ Enroll for Self-Paced Advance DSA course here: https://codeanddebug.in/course/zero-to-hero-python-dsa ๐Ÿ™ Thank you for supporting Code & Debug! Donโ€™t forget to like, share, and subscribe to our channel. Hit the ๐Ÿ”” bell icon to stay updated with our latest lectures. #Recursion #CountSubsequences #SubsetSum #Backtracking #PythonDSA #DSAPythonCourse #CodeAndDebug #CompetitiveProgramming #CodingInterviews #Part72


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