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Fundamentals of Data Structures and Algorithms: Fundamentals of Data Structures & Algorithms

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Curriculum For This Course
  • 1. Introduction 3m 20s
  • 2. How to calculate the time complexity 2m 52s
  • 3. The RAM model of computation 2m 7s
  • 4. Time complexity of Bubble sort algorithm 3m 25s
  • 5. Pseudo code : Bubble sort algorithm 3m 2s
  • 6. The Big O notation 3m 26s
  • 7. Using Big O notation : Examples 4m 41s
  • 8. Comparison of running times 4m 2s
  • 1. Selection Sort 2m 48s
  • 2. Selection Sort : Pseudocode 2m 34s
  • 3. Introduction to Insertion Sort 1m 56s
  • 4. Applying Insertion Sort algorithm to cue balls 2m 8s
  • 5. Insertion Sort: Pseudocode 2m 38s
  • 6. O(n²) sorting algorithms - Comparison 2m
  • 7. Stable Vs Unstable Sorts 3m 46s
  • 8. Searching elements in an un ordered array 3m 16s
  • 9. Searching elements in an ORDERED array 2m 33s
  • 10. Searching elements in an ORDERED array - contd. 5m 48s
  • 11. Inserting and Deleting items in an ORDERED array 2m 8s
  • 12. Sorting any type of object 1m 33s
  • 1. What is a Linked List? 3m 21s
  • 2. Implementing a Linked List in Java 56s
  • 3. Inserting a new Node 5m 25s
  • 4. Length of a Linked List 2m 11s
  • 5. Deleting the head node 2m 11s
  • 6. Searching for an Item 3m 11s
  • 7. Doubly Ended Lists 3m 6s
  • 8. Inserting data in a sorted Linked List 4m 38s
  • 9. Doubly Linked List 6m 28s
  • 10. Insertion Sort revisited 10m 32s
  • 1. Stacks 2m 41s
  • 2. Abstract Data Types 37s
  • 3. Implementing Stacks using Arrays 3m 21s
  • 4. Queues 2m 32s
  • 5. Queues using Arrays 5m 29s
  • 6. Double Ended Queues 1m 58s
  • 7. Double Ended Queues using Arrays 4m 20s
  • 1. Introduction 4m 33s
  • 2. Understanding Recursion 3m 4s
  • 3. Tail recursion 2m 8s
  • 4. Tower of Hanoi 8m 25s
  • 5. Tower of Hanoi - Implementation 2m 58s
  • 6. Merge Sort 4m 9s
  • 7. Merge Sort - Pseudocode 4m 24s
  • 8. Merge Step - Pseudocode 4m 32s
  • 9. Time Complexity of Merge Sort 2m 52s
  • 1. The Tree Data structure 3m 41s
  • 2. Binary Trees 3m 34s
  • 3. Binary Search Trees 2m 1s
  • 4. Finding an item in a Binary Search Tree 2m 24s
  • 5. Implementing the find method 3m 2s
  • 6. Inserting an item in a Binary Search Tree 3m 34s
  • 7. Deleting an Item : Case 1 6m 6s
  • 8. Deleting an Item - Case 2 2m 58s
  • 9. Deleting an Item - Case 3 3m 44s
  • 10. Deleting an Item - Soft Delete 1m 40s
  • 11. Finding smallest & largest values 2m 33s
  • 12. Tree Traversal : In Order 3m 19s
  • 13. Tree Traversal : Pre Order 1m 58s
  • 14. Tree Traversal : Post Order 56s
  • 15. Unbalanced Trees Vs Balanced Trees 2m 16s
  • 16. Height of a Binary Tree 1m 34s
  • 17. Time Complexity of Operations on Binary Search Trees 2m 16s
  • 1. Introduction 1m 27s
  • 2. QuickSort 4m 54s
  • 3. QuickSort: The partition step 2m 21s
  • 4. Shell Sort 5m 27s
  • 5. Shell Sort: Example 3m 28s
  • 6. Counting Sort 4m 50s
  • 7. Radix Sort 2m 27s
  • 8. Bucket Sort 3m 12s
  • 1. Introduction 4m 6s
  • 2. Deleting the root 1m 54s
  • 3. Inserting an item in a heap 1m 59s
  • 4. Heaps as Priority Queues 2m 30s
  • 5. Representing heaps using Arrays 1m 55s
  • 6. Heap Sort 2m 30s
  • 7. Building a heap 4m 7s
  • 1. Introduction 2m 41s
  • 2. Direct Access Tables 2m 4s
  • 3. Hashing 1m 37s
  • 4. Resolving collisions through chaining 4m 16s
  • 5. The Hash function 4m 16s
  • 6. Open Addressing to resolve collisions 2m 58s
  • 7. Strategies for Open Addressing 3m 19s
  • 8. Time Complexity: Open Addressing 3m 20s
  • 9. Conclusion 59s

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