Data Structure and Algorithms Analysis – Job Interview

Data Structure and Algorithms Analysis – Job Interview
Data Structure and Algorithms Analysis – Job Interview
English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 10.5 Hours | 1.48 GB

Write code that run faster, use less memory and prepare for Software Engineer Job Interview

This course prepared depending on my real Software Engineer job interviews experiences with Google, Microsoft, Amazon, and Snapchat.

In this course you will learn how to Analysis algorithms like Sorting, Searching, and Graph algorithms. And how to reduce the code complexity from one Big-O level to another level. Furthermore, you will learn different type of Data Structure for your code. Also you will learn how to find Big-O for every data structure, and how to apply correct Data Structure to your problem in Java. By the end you will be able to write code that run faster and use low memory. You Also will learn how to analysis problems using Dynamic programming.

We will discus code complexity in Different algorithms like Sorting algorithms ( Bubble, Merge, Heap, and quick sort) , searching algorithms ( Binary search, linear search, and Interpolation), Graph algorithms( Binary tree, DFS, BFS, Nearest Neighbor and Shortest path, Dijkstra’s Algorithm, and A* Algorithm). and Data Structure like Dynamic Array, Linked List, Stack, Queue, and Hash-Table

What you’ll learn

  • Write code that run faster, and use less memory
  • Prepare for job interview
  • Learn Data Structure and how to apply these Data Structures on problems in Java
  • Learn algorithms analysis and implementation.
  • Learn problem solving strategies
  • Learn how to find complexity of code and algorithms
Table of Contents

Introduction and Settings
1 Introduction
2 Interview triks
3 What you need to know before start
4 Complete Free Java course
5 Install Java JDK
6 Install Eclipse
7 Exercise files

Code Complexity
8 Code Complexity Big-O Omega and Theta
9 Big-O Examples

Data Structure
10 Why Data Structure
11 One-Dimension Array
12 One-Dimension Array implementation in Java
13 Two-Dimension Array
14 Two-Dimension Array implementation in Java
15 Dynamic Array
16 Dynamic Array implementation in Java
17 Linked List
18 Linked List implementation in Java
19 Doubly Linked List implementation in Java
20 Compare Linked List vs Array
21 HWCombine two Linked List (Google Interview Question)
22 Hash-Table
23 Hash-Table implementation in Java
24 Find unique number in Array (Amazon Phone Screen Interview )
25 Key Phrase problem TF-IDF
26 Stack
27 Stack implementation in Java Use Array
28 Stack implementation in Java Use Dynamic Array
29 Stack implementation in Java Use Linked List
30 Queue
31 Queue implementation in Java Use Array
32 Queue implementation in Java Use Dynamic Array
33 Queue implementation in Java Use Linked List
34 Priority queue
35 HWBest data structure for Array With Many Zeros (Google Interview Question)

Collections In Java
36 Data Structure functions in Java
37 ArrayList
38 LinkedList
39 HashMap
40 TreeSet HashSet
41 Stack
42 Queue and Priority Queue
43 Sort array of Objects
44 Recursion

Searching Algorithms
45 Linear Search
46 Linear Search implementation in Java
47 Binary Search
48 Binary Search implementation in Java
49 Interpolation Search
50 Interpolation Search implementation in Java

Sorting Algorithms
51 Bubble sort
52 Bubble Sort implementation in Java
53 Selection Sort
54 Select Sort implementation in Java
55 Quick Sort
56 Quick Sort implementation in Java
57 Merge Sort
58 Merge Sort implementation in Java
59 Heap Sort
60 Heap Sort implementation in Java

Tree Theory
61 Binary Tree and Binary Search Tree
62 Binary Search Tree implementation in Java
63 Problem of the Day
64 Red-Black Tree
65 Google Interview Determines if two BST are equal
66 HWFind SubTrees (Google Interview Question)

Graph Theory
67 Matrix and Adjacency List
68 Depth First Search(DFS)
69 DFS implementation in Java
70 Breadth First Search (BFS)
71 BFS implementation in Java
72 Backtracking
73 Preorder and PostOrder
74 HWVisit Cities in best Weather (Google Interview Question)
75 HW Nearest post office HW explain (Microsoft Interview Question)

Short Path in Graph Theory
76 Nearest Neighbor and Shortest path
77 Dijkstras Algorithm
78 A Algorithm

Dynamic Programming
79 Dynamic Programming concept
80 Edit distance
81 HWFind Word in list of characters
82 HWKnapsack problems
83 Knapsack solution in Java

NP Complete problems
84 NP Complete problems

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