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» » » Data Structures in Java - Part I (+INTERVIEW QUESTIONS)

Data Structures in Java - Part I (+INTERVIEW QUESTIONS)

Data Structures in Java - Part I (+INTERVIEW QUESTIONS)
Created by Holczer Balazs | Video: h264, 1280x720 | Audio: AAC 48KHz 2ch | Duration: 14:26 H/M | Lec: 165 | 2.58 GB | Language: English | Sub: English [Auto-generated]

Basic algorithms and data structures: AVL tree, binary search tree, array, linked list, stack, queue and hashmaps

What you'll learn
grasp the fundamentals of algorithms and data structures
develop your own algorithms that best fit to the personal need
detect non-optimal code snippets
get to know basic complexity related definitions
get to know linked lists
get to know arrays
get to know balanced trees: AVL trees and red-black trees
get to know hash tables
Core java
Eclipse or other IDE
This course is about data structures and algorithms. We are going to implement the problems in Java. The course takes approximately 14 hours to complete. It is highly recommended to type out these data structures several times on your own in order to get a good grasp of it.
Section 1:
data structures and abstract data types
what are arrays and linked lists
arrays and linked list related interview questions
Section 2:
what are stacks and queues
heap memory and stack memory
Section 3:
tree data structures
binary search trees
balanced search trees: AVL trees and red-black trees
splay trees (cache)
B-trees and their applications in memory
Section 4:
what are hashing and hashtables (hashmaps)
what are hash-functions
how to achieve O(1) running time complexity
Section 5 (BONUS):
what is LRU cache
LRU cache implementation
Section 6 (BONUS):
Fenwick trees (binary indexed trees)
binary indexed tree implementation
In each chapter you will learn 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.
Who this course is for?
This course is meant for everyone from scientists to software developers who want to get closer to algorithmic thinking in the main
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