Data Structures and Algorithms: Deep Dive Using Java

15h 53m 4s
English
Paid
April 26, 2024

So you've worked with the basics of data structures and algorithms in Java (or another OO programming language) but feel like you need a deeper knowledge of how things work. Maybe you have taken other courses on this topic that focus more on teaching how to pass job interview tests (theory) instead of how to make good choices for the programs you develop (implementation).

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Or maybe you are ready to move from a junior programming position to a more senior one and need to get skilled in advanced concepts like data structures, and how to apply them to your own projects.

Whatever the reason, if you are looking for a course that focus on the implementations to give you a complete understanding of how things work, then this is the course for you.

This course goes over the theory of how things work, but only to give you what you need to know to understand the implementation covered. 

Complete source code is included and available for you to download.

This is a hands-on course!  If you want to try understand things at a deep level, and work on implementations, rather than theory, then again, this is the course for you.

Topics covered:-

Arrays
Linked Lists
Trees
Hashtables
Stacks
Queues
Heaps
Sort algorithms
Search algorithms

The course also spends more time than most other courses of its kind looking at what’s available in the JDK. Students wanting to understand how things work "under the hood" will benefit enormously from this course.

Why learn about data structures and algorithms?

The reality is, the more you learn about data structures and algorithms, the better a programmer you become.

Why?

Because, data structures and algorithms are effectively patterns for solving problems.   You want to add as many of them as you can to your skill-set.  By doing so, you will find you solve more problems, and use the right tools for the job, in a more elegant way.  And you will learn a heap of them in this course.

Why enrolling in this course is the best decision you can make.

Your instructor, Sarah Ettritch has over 25 years’ software development experience and has been working with Java since JDK 1.1.  She has spent many years creating tools used by developers, which required a deep knowledge of data structures and algorithms, and is perfectly qualified to teach this course.

Most courses focus on giving you the theory of how things work, so that you can take an interview.  Whilst the theory is important, the knowledge of how to implement these data structures and algorithms are of vital importance.

This course goes over the theory of how things work, but only to give you what you need to know to understand the implementation covered.   The main focus of the course is to give you a real understanding of how things work under the hood, so that you can apply this to future programming projects.

If you want to actually understand how things work, and be able to take that understanding and apply it to your own programs, then this course is for you.

After completing this course, you will have a solid understanding of data structures and algorithms (both the theory, and the implementation).

The sooner you sign up for this course, the sooner you will have the skills and knowledge you need to increase your job or consulting opportunities.    Java developers with key skills and understanding of data structures and algorithms are in high demand and get paid extremely well.

If you are ready for that new job promotion or consulting opportunity, it's time to get started.

Requirements:
  • Previous experience with an object-oriented programming language, preferably Java (but any OO language is fine).

Who this course is for:

  • Developers who have some knowledge of Java (or another OO language) looking to understand data structures and algorithms at a deep level

What you'll learn:

  • Learn the strengths and weaknesses of a variety of data structures, so you can choose the best data structure for your data and applications
  • Code an implementation of each data structure, so you understand how they work under the covers
  • Learn many of the algorithms commonly used to sort data, so your applications will perform efficiently when sorting large datasets
  • Learn what’s available in the JDK for storing and sorting data, so you won’t waste time reinventing the wheel

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# Title Duration
1 Introduction to the Course 03:43
2 JDK8 for Windows 05:16
3 JDK8 for MAC 02:45
4 JDK8 for Linux 04:21
5 IntelliJ for Windows 09:55
6 IntelliJ for MAC 09:44
7 IntelliJ for Linux 10:23
8 Introduction to Data Structures 02:54
9 Introduction to Algorithms 04:16
10 Introduction to Arrays 00:54
11 Big-O Notation 14:10
12 A Quick Review of Arrays in Java 07:43
13 Arrays in Memory 09:03
14 Big-O Values for Array Operations 11:57
15 Introduction to Sort Algorithms 01:04
16 Bubble Sort (Theory) 08:51
17 Bubble Sort (Implementation) 11:35
18 Stable vs. Unstable Sort Algorithms 04:43
19 Selection Sort (Theory) 06:34
20 Selection Sort (Implementation) 05:03
21 Insertion Sort (Theory) 07:35
22 Insertion Sort (Implementation) 07:13
23 Shell Sort (Theory) 12:55
24 Shell Sort (Implementation) 10:50
25 Recursion 18:11
26 Merge Sort (Theory) 20:41
27 Merge Sort (Implementation) 28:10
28 Quick Sort (Theory) 08:59
29 Quick Sort (Implementation) 12:35
30 Counting Sort (Theory) 07:57
31 Counting Sort (Implementation) 08:36
32 Radix Sort (Theory) 11:13
33 Stable Counting Sort (Theory) 13:19
34 Radix Sort (Implementation) 14:06
35 Sorting Arrays Using the JDK 07:01
36 Sort Algorithms Challenge #1 01:12
37 Sort Algorithms Challenge #1 Solution 04:04
38 Sort Algorithms Challenge #2 00:50
39 Sort Algorithms Challenge #2 Solution 11:47
40 Sort Algorithms Challenge #3 01:13
41 Sort Algorithms Challenge #3 Solution 09:50
42 Introduction to Lists 02:50
43 Abstract Data Types 02:57
44 Array Lists 23:57
45 Vectors 06:49
46 Singly Linked Lists (Theory) 06:43
47 Singly Linked Lists (Implementation) 17:40
48 Doubly Linked Lists (Theory) 09:35
49 Doubly Linked Lists (Implementation) 21:48
50 The JDK LinkedList Class 12:35
51 Linked Lists Challenge #1 01:37
52 Linked Lists Challenge #1 Solution 09:30
53 Linked Lists Challenge #2 01:47
54 Linked Lists Challenge #2 Solution 07:32
55 Introduction to Stacks 00:39
56 Stacks (Theory) 07:23
57 Stacks Implementation (Array) 18:32
58 Stacks Implementation (Linked List) 12:00
59 Stacks Challenge 02:04
60 Stacks Challenge Solution 08:26
61 Introduction to Queues 00:27
62 Queues (Theory) 03:39
63 Queues (Array Implementation) 15:50
64 Circular Queue Implementation (Part One) 14:22
65 Circular Queue Implementation (Part Two) 20:32
66 Queues and the JDK 08:21
67 Queues Challenge 01:59
68 Queues Challenge Solution 08:53
69 Introduction to Hashtables 00:24
70 Hashtables (Theory) 08:26
71 Hashtables (Array Implementation) 13:54
72 Linear Probing 21:15
73 Linear Probing - Removing Items 09:40
74 Linear Probing - Rehashing 11:04
75 Chaining 21:25
76 Hashtables and the JDK 16:53
77 Bucket Sort (Theory) 06:36
78 Bucket Sort (Implementation) 09:05
79 Hashtables Challenge #1 01:55
80 Hashtables Challenge #1 Solution 02:40
81 Hashtables Challenge #2 01:38
82 Hashtables Challenge #2 Solution 07:56
83 Introduction to Search Algorithms 00:51
84 Linear Search Algorithm 03:52
85 Binary Search Algorithm 07:58
86 Binary Search (Implementation) 13:13
87 Introduction to Trees 00:56
88 Trees (Theory) 11:17
89 Binary Search Trees (Theory) 14:18
90 Binary Search Trees (Insertion) 10:51
91 Binary Search Trees (Traversal) 11:25
92 Binary Search Trees (Get, Min, Max) 10:29
93 Binary Search Trees (Delete Cases 1 and 2) 03:16
94 Binary Search Trees (Implement Cases 1 and 2) 09:12
95 Binary Search Trees (Delete Case 3) 08:52
96 Binary Seach Trees (Implement Case 3) 07:17
97 Trees and the JDK 03:45
98 Binary Search Trees Challenge #1 01:54
99 Binary Search Trees Challenge #1 Solution 02:50
100 Binary Search Trees Challenge #2 09:18
101 Introduction to Heaps 00:30
102 Heaps (Theory) 07:51
103 Storing Heaps as Arrays 07:55
104 Heaps (Insert) 09:03
105 Heaps (Delete Theory) 06:56
106 Heaps (Delete) 20:07
107 Heaps (Peek) 05:20
108 Priority Queues 12:01
109 Heapsort (Theory) 04:55
110 Heapsort (Implementation) 07:17
111 Sets 02:52
112 Course Wrap-Up 01:25
113 Bonus - Please Watch! 00:49

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