IT & Software [udemy.com] Data Structures in Java - Part I (+INTERVIEW QUESTIONS)

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27 Авг 2018
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What you'll learn
  • 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
  • grasp the fundamentals of algorithms and data structures
Requirements
  • Eclipse or other IDE
  • Core java
Desсription

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
  • heaps
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.

Thanks for joining the course, let's get started!

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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