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8/13/2020
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The Ultimate Data Structures & Algorithms: Part 2 is a practical training course in data structure and algorithms that helps you to write better and faster. Have you studied computer science but failed to understand the subject of data structure and algorithms? Or did you give up your job interview because of a lack of information about the building and the algorithm? If the answer is yes, this course can completely solve your problem.
Data structures and algorithms are models for solving programming problems. Programmers with sufficient knowledge of data structure and algorithms solve problems better than others. In this course, you will learn about nonlinear data structures and learn topics such as binary tree, AVL tree, stacks, try, and graphs. The course instructor uses Java language to explain data structure and algorithm concepts, but you can use the course techniques in any programming language.
Familiarity with nonlinear data structure
Better and faster coding
Increase programming problem solving skills
Mastery of the basic concepts of computer science
Familiarity with the most popular algorithms
Work with essential data structure concepts
Familiarity with binary tree and AVL tree
English language
Duration: 6 hours
Number of courses: 130
Level of education: Intermediate
Instructor: Mosh Hamedani
File format: mp4
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) 10- 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 the Root (4:37) 19- Level Order Traversal (2:55) 20- Trees- Exercises 21- Summary (1:22)
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)
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
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 (Recursive) (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
In this course, I 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.
After Extract, watch with your favorite Player.
English subtitle
Quality: 1080p
Changes:
Version 2020/1 Compared to 2019/9, one lesson and subtitles of all lessons have been added.
Friends who have purchased the previous version should submit their request in the Contact Us section to receive subtitles only.
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