Design Thinking Based Learning Approach | Quick Sort | Data Structures | SNS Institutions

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Quick Sort is one of the most efficient and widely used sorting algorithms in computer science, and in this video, we’ll explore it in a simple yet detailed way to help you fully understand how it works. Quick Sort is based on the powerful concept of divide and conquer, which means it breaks a large problem into smaller, more manageable parts. The algorithm works by selecting a pivot element, partitioning the array into two subarrays—one containing elements smaller than the pivot and the other containing elements greater than the pivot—and then recursively sorting these subarrays. This method allows Quick Sort to achieve excellent performance in most real-world scenarios, making it faster than many other sorting techniques like Bubble Sort and Insertion Sort. In this tutorial, we’ll go through the entire process step-by-step, using easy-to-follow explanations, visual demonstrations, and coding examples to make the concept crystal clear. You’ll learn about how to choose a good pivot, how the partitioning works, and how recursive calls organize the data efficiently. We’ll also discuss the time complexity of Quick Sort, which is O(n log n) in the best and average cases and O(n²) in the worst case, and compare it with other algorithms such as Merge Sort. By the end of this video, you’ll not only understand the theory behind Quick Sort but also know how to implement it in programming languages like Python, C++, or Java. Make sure to like, comment, and subscribe for more tutorials on data structures and algorithms!