[Download Now] Holczer Balazs – Algorithms and Data Structures in Java – Part I
PLEASE CHECK ALL CONTENTS HERE:PLEASE CHECK ALL CONTENTS HERE:
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Salepage_https://globalsoftwaresupport.teachable.com/p/algorithms-and-data-structures-in-java-part-iSalepage_https://globalsoftwaresupport.teachable.com/p/algorithms-and-data-structures-in-java-part-i
Archive: https://archive.fo/wip/B8CSL Archive: https://archive.fo/wip/B8CSL
This course is about data structures and algorithms. We are going to implement the problems in Java, but I try to do it as generic as possible: so the core of the algorithms can be used in C++ or Python. The course takes approximately 11 hours to complete. I highly recommend typing out these data structures several times on your own in order to get a good grasp of it.This course is about data structures and algorithms. We are going to implement the problems in Java, but I try to do it as generic as possible: so the core of the algorithms can be used in C++ or Python. The course takes approximately 11 hours to complete. I highly recommend typing out these data structures several times on your own in order to get a good grasp of it.
In the first part of the course we are going to learn about basic data structures such as linked lists, stacks and queues, heaps and some advanced ones such as AVL trees, red-black trees or hash tables. We will try to optimize each data structure ( for example avoiding obsolete references ) as much as possible.In the first part of the course we are going to learn about basic data structures such as linked lists, stacks and queues, heaps and some advanced ones such as AVL trees, red-black trees or hash tables. We will try to optimize each data structure ( for example avoiding obsolete references ) as much as possible.
In each chapter I am going to talk about the theoretical background of each algorithm or data structure, then we are going to write the code on a step by step basis in Eclipse, Java.In each chapter I am going to talk about the theoretical background of each algorithm or data structure, then we are going to write the code on a step by step basis in Eclipse, Java.
Most of the advanced algorithms relies heavily on these topics so it is definitely worth understanding the basics. These principles can be used in several fields: in investment banking, artificial intelligence or electronic trading algorithms on the stock market.Most of the advanced algorithms relies heavily on these topics so it is definitely worth understanding the basics. These principles can be used in several fields: in investment banking, artificial intelligence or electronic trading algorithms on the stock market.
Course Curriculum
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IntroductionIntroduction
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Introduction (1:13)Introduction (1:13)
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Why to use data structures (3:54)Why to use data structures (3:54)
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Data structures and abstract data types (3:58)Data structures and abstract data types (3:58)
ArraysArrays
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Arrays introduction – basics (5:55)Arrays introduction – basics (5:55)
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Arrays introduction – operations (5:54)Arrays introduction – operations (5:54)
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Using arrays (9:51)Using arrays (9:51)
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ArraysLists in Java (8:42)ArraysLists in Java (8:42)
Linked ListsLinked Lists
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Linked lists theory – basics (7:09)Linked lists theory – basics (7:09)
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Linked list theory – operations (9:32)Linked list theory – operations (9:32)
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Linked list theory – doubly linked lists (1:40)Linked list theory – doubly linked lists (1:40)
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Linked list theory – linked lists versus arrays (6:36)Linked list theory – linked lists versus arrays (6:36)
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Linked list implementation I (4:47)Linked list implementation I (4:47)
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Linked list implementation II (11:40)Linked list implementation II (11:40)
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Linked list implementation III (5:59)Linked list implementation III (5:59)
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Doubly linked list introduction (7:55)Doubly linked list introduction (7:55)
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Linked lists in java.util (8:14)Linked lists in java.util (8:14)
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Stacks & QueuesStacks & Queues
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Stack introduction (4:01)Stack introduction (4:01)
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Stacks in memory management ( stacks, heaps ) (7:23)Stacks in memory management ( stacks, heaps ) (7:23)
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Stacks and recursive method calls (7:02)Stacks and recursive method calls (7:02)
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Stack implementation with linked list I (7:28)Stack implementation with linked list I (7:28)
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Stack implementation with linked list II (3:38)Stack implementation with linked list II (3:38)
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Stack implementation with arrays (11:01)Stack implementation with arrays (11:01)
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Dijkstra’s interpreter introduction (1:18)Dijkstra’s interpreter introduction (1:18)
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Dijkstra’s interpreter implementation (9:12)Dijkstra’s interpreter implementation (9:12)
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Java built in java.util.Stack (5:09)Java built in java.util.Stack (5:09)
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Queues introduction (5:12)Queues introduction (5:12)
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Queue implementation with linked list (9:43)Queue implementation with linked list (9:43)
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Java built in java.util.Queue (6:31)Java built in java.util.Queue (6:31)
Binary Search TreesBinary Search Trees
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Binary search trees theory – basics (10:23)Binary search trees theory – basics (10:23)
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Binary search trees theory – search, insert (4:25)Binary search trees theory – search, insert (4:25)
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Binary search trees theory – delete (6:08)Binary search trees theory – delete (6:08)
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Binary search trees theory – in-order traversal (4:25)Binary search trees theory – in-order traversal (4:25)
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Binary search trees theory – running times (2:10)Binary search trees theory – running times (2:10)
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Binary search trees implementation I – Node, Tree (7:02)Binary search trees implementation I – Node, Tree (7:02)
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Binary search trees implementation II – insertion (9:55)Binary search trees implementation II – insertion (9:55)
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Binary search tree implementation III – maximum, minimum (7:24)Binary search tree implementation III – maximum, minimum (7:24)
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Binary search tree implementation IV – traversal (5:41)Binary search tree implementation IV – traversal (5:41)
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Binary search tree implementation V – remove (9:25)Binary search tree implementation V – remove (9:25)
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Binary search tree implementation VI – remove II (5:54)Binary search tree implementation VI – remove II (5:54)
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Custom objects in a tree (6:44)Custom objects in a tree (6:44)
Balanced Trees: AVL TreesBalanced Trees: AVL Trees
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AVL trees introduction – motivation (4:13)AVL trees introduction – motivation (4:13)
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AVL trees introduction – basics (5:21)AVL trees introduction – basics (5:21)
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AVL trees introduction – height (8:44)AVL trees introduction – height (8:44)
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AVL trees introduction – rotations cases (10:17)AVL trees introduction – rotations cases (10:17)
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AVL trees introduction – illustration (10:50)AVL trees introduction – illustration (10:50)
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AVL trees introduction – sorting (3:38)AVL trees introduction – sorting (3:38)
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AVL implementation – Node and Tree (3:21)AVL implementation – Node and Tree (3:21)
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AVL implementation – balance and height parameters (4:45)AVL implementation – balance and height parameters (4:45)
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AVL implementation – implementing the rotations (7:36)AVL implementation – implementing the rotations (7:36)
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AVL implementation – insertion I (6:03)AVL implementation – insertion I (6:03)
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AVL implementation – insertion II (8:52)AVL implementation – insertion II (8:52)
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AVL implementation – testing (3:19)AVL implementation – testing (3:19)
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AVL tree remove introduction (6:35)AVL tree remove introduction (6:35)
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AVL tree remove implementation I (8:31)AVL tree remove implementation I (8:31)
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AVL tree generic implementation (3:55)AVL tree generic implementation (3:55)
Balanced Trees: Red-Black TreesBalanced Trees: Red-Black Trees
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Red-black trees introduction – basics (10:38)Red-black trees introduction – basics (10:38)
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The logic behind red-black trees (4:15)The logic behind red-black trees (4:15)
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Red-black trees rotations- cases I (5:10)Red-black trees rotations- cases I (5:10)
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Red-black trees rotations- cases II (4:25)Red-black trees rotations- cases II (4:25)
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Red-black trees rotations- cases III (3:17)Red-black trees rotations- cases III (3:17)
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Red-black trees rotations- cases IV (2:45)Red-black trees rotations- cases IV (2:45)
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Red-black trees introduction – example I (4:47)Red-black trees introduction – example I (4:47)
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Red-black trees introduction – example II (4:19)Red-black trees introduction – example II (4:19)
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Red-black tree versus AVL tree (3:25)Red-black tree versus AVL tree (3:25)
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Red-black tree implementation I – Node class (4:28)Red-black tree implementation I – Node class (4:28)
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Red-black tree implementation II – traverse (2:06)Red-black tree implementation II – traverse (2:06)
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Red-black tree implementation III – insert (3:40)Red-black tree implementation III – insert (3:40)
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Red-black tree implementation IV – rotate left / right (5:48)Red-black tree implementation IV – rotate left / right (5:48)
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Red-black tree implementation V – fixing the violations (9:52)Red-black tree implementation V – fixing the violations (9:52)
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Red-black tree implementation VI – fixing the violations (5:52)Red-black tree implementation VI – fixing the violations (5:52)
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Red-black tree implementation VII – testing (1:59)Red-black tree implementation VII – testing (1:59)
Splay TreesSplay Trees
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Splay tree introduction I – basics (12:49)Splay tree introduction I – basics (12:49)
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Splay tree introduction II – example (3:52)Splay tree introduction II – example (3:52)
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Splay tree implementation I – find, rotate (9:44)Splay tree implementation I – find, rotate (9:44)
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Splay tree implementation II – spalying (3:34)Splay tree implementation II – spalying (3:34)
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Splay tree implementation III – testing (5:50)Splay tree implementation III – testing (5:50)
HeapsHeaps
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Priority queues introduction (8:13)Priority queues introduction (8:13)
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Heap introduction – basics (8:14)Heap introduction – basics (8:14)
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Heap introduction – array representation (9:17)Heap introduction – array representation (9:17)
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Heap introduction – remove operation (4:43)Heap introduction – remove operation (4:43)
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Heap introduction – heapsort (5:13)Heap introduction – heapsort (5:13)
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Heap introduction – running times (5:05)Heap introduction – running times (5:05)
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Other types of heaps: binomial and Fibonacci heap (2:59)Other types of heaps: binomial and Fibonacci heap (2:59)
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Heap implementation I (8:28)Heap implementation I (8:28)
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Heap implementation II (6:38)Heap implementation II (6:38)
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Heap implementation III (5:00)Heap implementation III (5:00)
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Heaps in java.util.PriorityQueue (8:33)Heaps in java.util.PriorityQueue (8:33)
B-TreesB-Trees
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B-tree introduction – basics (13:01)B-tree introduction – basics (13:01)
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B-tree and external memory (4:07)B-tree and external memory (4:07)
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Disk access times (5:41)Disk access times (5:41)
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B-tree introduction – search (2:46)B-tree introduction – search (2:46)
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B-tree introduction – insertion (7:10)B-tree introduction – insertion (7:10)
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B-tree introduction – deletion (5:30)B-tree introduction – deletion (5:30)
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In-order traversal (4:06)In-order traversal (4:06)
HashtablesHashtables
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Associative array ADT (2:37)Associative array ADT (2:37)
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Hashtables introduction – basics (9:04)Hashtables introduction – basics (9:04)
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Hashtables introduction – collisions (6:59)Hashtables introduction – collisions (6:59)
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Hashtables introduction – load factor & dynamic resizing (6:03)Hashtables introduction – load factor & dynamic resizing (6:03)
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Chaining method summary (4:05)Chaining method summary (4:05)
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Chaining implementation I – put (9:16)Chaining implementation I – put (9:16)
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Chaining implementation II – get (4:27)Chaining implementation II – get (4:27)
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Chaining implementation III – testingChaining implementation III – testing
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Linear probing summary (3:59)Linear probing summary (3:59)
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Linear probing implementation I – put (5:32)Linear probing implementation I – put (5:32)
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Linear probing implementation II – get (2:57)Linear probing implementation II – get (2:57)
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Linear probing implementation III – testing (4:44)Linear probing implementation III – testing (4:44)
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Generic linear probing implementation I – basics (6:44)Generic linear probing implementation I – basics (6:44)
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Generic linear probing implementation II – get (4:14)Generic linear probing implementation II – get (4:14)
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Generic linear probing implementation III – put (5:35)Generic linear probing implementation III – put (5:35)
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Generic linear probing implementation IV – remove (6:26)Generic linear probing implementation IV – remove (6:26)
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Generic linear probing implementation V – resize (5:30)Generic linear probing implementation V – resize (5:30)
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Generic linear probing implementation VI – testing (2:39)Generic linear probing implementation VI – testing (2:39)
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Generic linear probing implementation – hashCode (2:05)Generic linear probing implementation – hashCode (2:05)
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Maps in Java Collections (5:52)Maps in Java Collections (5:52)
Least Recently Used (LRU) CacheLeast Recently Used (LRU) Cache
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Why to use cache? (3:25)Why to use cache? (3:25)
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LRU cache introduction (8:06)LRU cache introduction (8:06)
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LRU cache implementation I (4:22)LRU cache implementation I (4:22)
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LRU cache implementation II (11:18)LRU cache implementation II (11:18)
Course MaterialsCourse Materials
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SlidesSlides
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Source codeSource code
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