Fundamentals of Data Structures and Algorithms: Fundamentals of Data Structures & Algorithms
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92 Lectures
4h 53m 52s
Prepare for your Microsoft examination with our training course. The No_code course contains a complete batch of videos that will provide you with profound and thorough knowledge related to Microsoft certification exam. Pass the Microsoft No_code test with flying colors.
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Curriculum For This Course
- 1. Introduction 1m 8s
- 2. Euclid's algorithm 4m 49s
- 3. Bubble Sort algorithm 2m 52s
- 4. Why study data structures & algorithms 3m 10s
- 5. Correctness of an algorithm 1m 35s
- 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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