[Download Now] Holczer Balazs – Algorithms and Data Structures in Java – Part I

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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.

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.

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

Introduction

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Introduction (1:13)
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Why to use data structures (3:54)
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Data structures and abstract data types (3:58)

Arrays

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Arrays introduction – basics (5:55)
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Arrays introduction – operations (5:54)
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Using arrays (9:51)
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ArraysLists in Java (8:42)

Linked Lists

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Linked lists theory – basics (7:09)
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Linked list theory – operations (9:32)
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Linked list theory – doubly linked lists (1:40)
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Linked list theory – linked lists versus arrays (6:36)
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Linked list implementation I (4:47)
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Linked list implementation II (11:40)
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Linked list implementation III (5:59)
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Doubly linked list introduction (7:55)
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Linked lists in java.util (8:14)

Stacks & Queues

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Stack introduction (4:01)
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Stacks in memory management ( stacks, heaps ) (7:23)
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Stacks and recursive method calls (7:02)
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Stack implementation with linked list I (7:28)
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Stack implementation with linked list II (3:38)
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Stack implementation with arrays (11:01)
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Dijkstra’s interpreter introduction (1:18)
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Dijkstra’s interpreter implementation (9:12)
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Java built in java.util.Stack (5:09)
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Queues introduction (5:12)
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Queue implementation with linked list (9:43)
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Java built in java.util.Queue (6:31)

Binary Search Trees

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Binary search trees theory – basics (10:23)
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Binary search trees theory – search, insert (4:25)
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Binary search trees theory – delete (6:08)
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Binary search trees theory – in-order traversal (4:25)
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Binary search trees theory – running times (2:10)
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Binary search trees implementation I – Node, Tree (7:02)
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Binary search trees implementation II – insertion (9:55)
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Binary search tree implementation III – maximum, minimum (7:24)
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Binary search tree implementation IV – traversal (5:41)
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Binary search tree implementation V – remove (9:25)
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Binary search tree implementation VI – remove II (5:54)
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Custom objects in a tree (6:44)

Balanced Trees: AVL Trees

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AVL trees introduction – motivation (4:13)
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AVL trees introduction – basics (5:21)
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AVL trees introduction – height (8:44)
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AVL trees introduction – rotations cases (10:17)
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AVL trees introduction – illustration (10:50)
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AVL trees introduction – sorting (3:38)
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AVL implementation – Node and Tree (3:21)
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AVL implementation – balance and height parameters (4:45)
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AVL implementation – implementing the rotations (7:36)
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AVL implementation – insertion I (6:03)
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AVL implementation – insertion II (8:52)
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AVL implementation – testing (3:19)
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AVL tree remove introduction (6:35)
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AVL tree remove implementation I (8:31)
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AVL tree generic implementation (3:55)

Balanced Trees: Red-Black Trees

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Red-black trees introduction – basics (10:38)
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The logic behind red-black trees (4:15)
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Red-black trees rotations- cases I (5:10)
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Red-black trees rotations- cases II (4:25)
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Red-black trees rotations- cases III (3:17)
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Red-black trees rotations- cases IV (2:45)
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Red-black trees introduction – example I (4:47)
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Red-black trees introduction – example II (4:19)
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Red-black tree versus AVL tree (3:25)
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Red-black tree implementation I – Node class (4:28)
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Red-black tree implementation II – traverse (2:06)
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Red-black tree implementation III – insert (3:40)
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Red-black tree implementation IV – rotate left / right (5:48)
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Red-black tree implementation V – fixing the violations (9:52)
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Red-black tree implementation VI – fixing the violations (5:52)
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Red-black tree implementation VII – testing (1:59)

Splay Trees

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Splay tree introduction I – basics (12:49)
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Splay tree introduction II – example (3:52)
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Splay tree implementation I – find, rotate (9:44)
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Splay tree implementation II – spalying (3:34)
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Splay tree implementation III – testing (5:50)

Heaps

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Priority queues introduction (8:13)
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Heap introduction – basics (8:14)
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Heap introduction – array representation (9:17)
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Heap introduction – remove operation (4:43)
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Heap introduction – heapsort (5:13)
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Heap introduction – running times (5:05)
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Other types of heaps: binomial and Fibonacci heap (2:59)
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Heap implementation I (8:28)
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Heap implementation II (6:38)
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Heap implementation III (5:00)
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Heaps in java.util.PriorityQueue (8:33)

B-Trees

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B-tree introduction – basics (13:01)
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B-tree and external memory (4:07)
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Disk access times (5:41)
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B-tree introduction – search (2:46)
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B-tree introduction – insertion (7:10)
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B-tree introduction – deletion (5:30)
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In-order traversal (4:06)

Hashtables

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Associative array ADT (2:37)
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Hashtables introduction – basics (9:04)
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Hashtables introduction – collisions (6:59)
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Hashtables introduction – load factor & dynamic resizing (6:03)
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Chaining method summary (4:05)
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Chaining implementation I – put (9:16)
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Chaining implementation II – get (4:27)
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Chaining implementation III – testing
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Linear probing summary (3:59)
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Linear probing implementation I – put (5:32)
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Linear probing implementation II – get (2:57)
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Linear probing implementation III – testing (4:44)
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Generic linear probing implementation I – basics (6:44)
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Generic linear probing implementation II – get (4:14)
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Generic linear probing implementation III – put (5:35)
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Generic linear probing implementation IV – remove (6:26)
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Generic linear probing implementation V – resize (5:30)
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Generic linear probing implementation VI – testing (2:39)
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Generic linear probing implementation – hashCode (2:05)
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Maps in Java Collections (5:52)

Least Recently Used (LRU) Cache

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Why to use cache? (3:25)
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LRU cache introduction (8:06)
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LRU cache implementation I (4:22)
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LRU cache implementation II (11:18)

Course Materials

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Slides
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Source code

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