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## Description

The Ultimate Data Structures & Algorithms: Part 2 is a hands-on training in data construction and algorithms that helps you get better and faster coding. Are you also a computer science major, but have failed to understand the data structure and algorithm well? Or your job interview for lack of building information and not having a good algorithm? If your answer is positive, this period can completely eliminate your problem.

Data structures and algorithms are models for solving programming problems. Programmers who have a good understanding of data structures and algorithms solve problems better than others. In this course, you’ll learn about nonlinear data structures and learn topics like binary tree , AVL tree , stack, try, and graph. The instructor uses Java to explain the concepts of data structure and algorithm, but you can use the techniques in any programming language.

### Courses taught in this course:

• Introduction to Nonlinear Data Structure
• Better and faster coding
• Increase your problem solving skills
• Mastering the basic concepts of computer science
• Introduction to the most popular algorithms
• Work with the essential concepts of data construction
• Introduction to binary tree and AVL tree

### Course Profile The Ultimate Data Structures & Algorithms: Part 2:

• English language
• Duration: 6 hours
• Number of lessons: 130
• Level of education: Intermediate
• Instructor: Mosh Hamedani
• File format: mp4

### Course headings

Getting Started
1- Introduction (0:50)
2- Source Code
Binary Trees (73m)
1- Introduction (0:55)
2- What Are Trees (5:36)
3- Exercise- Populating a Binary Search Tree
4- Exercise- Building a Tree (2:41)
5- Solution-insert () (7:44)
6- Solution- find () (2:00)
7- Traversing Trees 5:58
8- Exercise- Tree Traversal
9- Recursion (5:39)
Depth First Traversals 5:23
11- Depth and Height of Nodes 7:06
12- Minimum Value in a Tree (7:37)
13- Exercise- Equality Checking (0:45)
14- Solution- Equality Checking (4:08)
15- Exercise- Validating Binary Search Trees (4:14)
16- Solution- Validating Binary Search Trees (4:18)
17- Exercise- Nodes at K Distance (1:48)
18- Solution- Nodes at K Distance from Root 4:37
19- Level Order Traversal (2:55)
20- Trees- Exercises
21- Summary (1:22)

##### AVL Trees (49m)

1- Introduction (0:31)
2- Balanced and Unbalanced Trees (3:01)
3- Rotations (5:02)
4- AVL Trees (4:04)
5- Exercise: AVL Rotations
6- Exercise- Building an AVL Tree (1:11)
7- Solution-insert () (8:47)
8- Exercise- Height Calculation (1:24)
9- Solution- Height Calculation (2:43)
10- Exercise- Balance Factor (2:04)
11- Solution- Balance Factor (4:01)
12- Exercise- Detecting Rotations (2:54)
13- Solution- Detecting Rotations (3:32)
14- Exercise- Implementing Rotations (3:51)
15- Solution- Implementing Rotations (5:40)
16- AVL Trees- Exercises
17- Summary (1:01)
A Quick Note
Heaps (53m)
1- Introduction (0:21)
2- What are Heaps (6:28)
3- Exercise- Working with Heaps
4- Exercise- Building a Heap (1:55)
5- Solution-insert () (8:24)
6- Solution-remove () (7:07)
7- Solution – Edge Cases (6:11)
8- Heap Sort (2:29)
9- Priority Queues (5:04)
10- Exercise- Heapify (1:26)
11- Solution- Heapify (7:12)
12- Solution-Optimization (2:42)
13- Exercise- Kth Largest Item (0:31)
14- Solution- Kth Largest Item (3:47)
15- Heaps- Exercises
16- Summary (1:19)

##### Tries (46m)

1- Introduction (0:30)
2- What are Tries (3:50)
3- Exercise- Populating a Trie
4- Exercise- Building a Trie (3:03)
5- Solution- Building a Trie (5:44)
6- An Implementation with a HashTable (1:50)
7- A Better Abstraction (5:28)
8- Exercise- Looking Up a Word (1:12)
9- Solution- Looking Up a Word (2:35)
10- Traversals (3:35)
11- Exercise- Removing a Word (1:53)
12- Solution- Removing a Word (8:14)
13- Exercise- Auto Completion (2:51)
14- Solution- Auto Completion (5:59)
15- Tries- Exercises
16- Summary (0:45)
A Quick Note

##### Graphs (66m)

1- Introduction (0:26)
2- What are Graphs (2:09)
3- Adjacency Matrix (4:14)
4- Adjacency List (6:32)
5- Exercise- Building a Graph (1:50)
6- Solution- Adding Nodes and Edges (7:34)
7- Solution- Removing Nodes and Edges (4:48)
8- Traversal Algorithms (3:58)
9- Exercise- Traversal Algorithms
10- Exercise- Depth-first Traversal (1:29)
11- Solution- Depth-first Traversal (Recursive) (3:44)
12- Exercise- Depth-first Traversal (Iterative) (2:44)
13- Solution- Depth-first Traversal (Iterative) (3:59)
14- Exercise- Breadth-first Traversal (Iterative) (1:18)
15- Solution- Breadth-first Traversal (2:41)
16- Exercise- Topological Sorting (5:06)
17- Solution- Topological Sort (4:05)
18- Exercise- Cycle Detection (Directed Graphs) (3:42)
19- Solution- Cycle Detection (Directed Graphs) 6:26
20- Graphs Summary 1:02
Undirected Graphs (59m)
1- Introduction (0:26)
2- Exercise- Weighted Graphs (1:30)
3- Solution- Weighted Graphs (5:20)
4- An Object-Oriented Solution (6:13)
5- Dijkstra’s Shortest Path Algorithm (4:35)
6- Exercise- Getting the Shortest Distance (6:08)
7- Solution- The Shortest Distance (5:27)
8- Solution- Shortest Path (7:53)
9- Exercise- Cycle Detection (Undirected Graphs) (2:03)
10- Solution- Cycle Detection (Undirected Graphs) (4:42)
11- Minimum Spanning Tree (1:56)
12- Exercise- Prim’s Algorithm (2:45)
13- Solution- Prim’s Algorithm (10:39)
14- Thank You

### Course prerequisites

In this course, I will use Java to teach the concepts but you can apply these concepts in any programming language. Our focus is on data structures and algorithms, not programming languages ​​and tools.

All you need to take this course are some basic programming skills. If you know variables, loops, and conditional statements, you’re good. If you need a quick refresher to get up to speed with Java syntax, you can watch the first part of my Java series.

Ideally, you should have taken the first part of this series as the concepts and exercises in this part are more complex than those covered in the first part.

### Images of The Ultimate Data Structures & Algorithms: Part 2 ### Installation guide

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English subtitle

Quality: 1080p

Changes:

Version 2020/1 compared to 2019/9 has added a whole lesson and subtitle.

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