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Data Structures & Algorithms Complete Course
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🚀 Ready for diving deeper and apply your data structures & algorithms knowledge? enroll in my complete data structures and algorithms course now:
Being proficient in data structures and algorithms is a great advantage for any programmer as it opens many career opportunities and improves problem solving skills.
In this course you will learn all the concepts about Big O notations, data structures and algorithms so that you can understand them very well and use them in whatever programming language you use.
So get ready, prepare your favourite drink and let’s get started.
Chapters:
00:00:00 Introduction
00:00:33 What are data structures ?
00:01:26 What are algorithms ?
00:02:08 Big O Notation
00:03:45 Linear Complexity aka O(n)
00:05:42 Constant Complexity aka O(1)
00:07:35 Quadratic Complexity aka O(n^2)
00:09:35 Logarithmic Complexity aka O(logn)
00:11:59 Constants in Big O Notation
00:13:40 Dominant and non-dominant factors in Big O Notation
00:14:43 Complexities comparison
00:16:00 Linked Lists
00:17:16 Adding elements to Linked Lists
00:19:16 Removing elements from Linked Lists
00:21:34 Time and space complexities of Linked Lists operations
00:25:24 When to use Linked Lists ?
00:26:21 Doubly Linked Lists
00:27:11 Time and space complexities of Doubly Linked Lists operations
00:28:54 Stacks
00:30:29 Queues
00:31:28 Trees
00:32:14 Binary Trees
00:34:21 Binary Search Tree
00:37:15 Heaps
00:39:32 Inserting elements in Heaps
00:43:20 Pop operation in Heaps
00:46:17 Heap operations time and space complexities
00:47:09 Hash Tables
00:51:20 Hash Tables time and space complexities
00:52:43 Graphs
00:54:18 Graphs: Adjacency Matrix
00:56:19 Graphs: Adjacency List
00:57:36 Graphs time and space complexities
01:02:13 Tries
01:03:57 Tries: insert operation
01:07:48 Search operation in Tries
01:10:46 Tries time and space complexities
01:12:07 Linear Search
01:14:30 Binary Search
01:18:16 Searching algorithms time and space complexities
01:19:19 Bubble Sort
01:21:44 Insertion Sort
01:23:51 Selection Sort
01:25:22 Merge Sort
01:27:20 Sorting algorithms space and time complexities
01:30:40 Recursion
01:32:54 Call Stack
01:35:51 Recursion time and space complexities
01:37:09 What is a Stack Overflow
01:38:36 Tree traversal algorithms
01:39:35 Preorder traversal algorithm
01:40:47 Inorder traversal algorithm
01:43:05 Postorder traversal algorithm
01:44:14 Tree traversal time and space complexities
01:45:17 Graph traversal algorithms
01:45:44 Breadth first search
01:47:35 Depth first search
01:49:14 Graph traversal algorithms time and space complexities
#datastructures #algorithms #computerscience #datastructuresandalgorithms
Being proficient in data structures and algorithms is a great advantage for any programmer as it opens many career opportunities and improves problem solving skills.
In this course you will learn all the concepts about Big O notations, data structures and algorithms so that you can understand them very well and use them in whatever programming language you use.
So get ready, prepare your favourite drink and let’s get started.
Chapters:
00:00:00 Introduction
00:00:33 What are data structures ?
00:01:26 What are algorithms ?
00:02:08 Big O Notation
00:03:45 Linear Complexity aka O(n)
00:05:42 Constant Complexity aka O(1)
00:07:35 Quadratic Complexity aka O(n^2)
00:09:35 Logarithmic Complexity aka O(logn)
00:11:59 Constants in Big O Notation
00:13:40 Dominant and non-dominant factors in Big O Notation
00:14:43 Complexities comparison
00:16:00 Linked Lists
00:17:16 Adding elements to Linked Lists
00:19:16 Removing elements from Linked Lists
00:21:34 Time and space complexities of Linked Lists operations
00:25:24 When to use Linked Lists ?
00:26:21 Doubly Linked Lists
00:27:11 Time and space complexities of Doubly Linked Lists operations
00:28:54 Stacks
00:30:29 Queues
00:31:28 Trees
00:32:14 Binary Trees
00:34:21 Binary Search Tree
00:37:15 Heaps
00:39:32 Inserting elements in Heaps
00:43:20 Pop operation in Heaps
00:46:17 Heap operations time and space complexities
00:47:09 Hash Tables
00:51:20 Hash Tables time and space complexities
00:52:43 Graphs
00:54:18 Graphs: Adjacency Matrix
00:56:19 Graphs: Adjacency List
00:57:36 Graphs time and space complexities
01:02:13 Tries
01:03:57 Tries: insert operation
01:07:48 Search operation in Tries
01:10:46 Tries time and space complexities
01:12:07 Linear Search
01:14:30 Binary Search
01:18:16 Searching algorithms time and space complexities
01:19:19 Bubble Sort
01:21:44 Insertion Sort
01:23:51 Selection Sort
01:25:22 Merge Sort
01:27:20 Sorting algorithms space and time complexities
01:30:40 Recursion
01:32:54 Call Stack
01:35:51 Recursion time and space complexities
01:37:09 What is a Stack Overflow
01:38:36 Tree traversal algorithms
01:39:35 Preorder traversal algorithm
01:40:47 Inorder traversal algorithm
01:43:05 Postorder traversal algorithm
01:44:14 Tree traversal time and space complexities
01:45:17 Graph traversal algorithms
01:45:44 Breadth first search
01:47:35 Depth first search
01:49:14 Graph traversal algorithms time and space complexities
#datastructures #algorithms #computerscience #datastructuresandalgorithms
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