Beginning Java Data Structures and Algorithms

Beginning Java Data Structures and Algorithms, available at $49.99, has an average rating of 4.5, with 35 lectures, 6 quizzes, based on 5 reviews, and has 54 subscribers.

You will learn about Understand some of the fundamental concepts behind key algorithms Express space and time complexities using Big O notation. Correctly implement classic sorting algorithms such as merge and quicksort Correctly implement basic and complex data structures Learn about different algorithm design paradigms, such as greedy, divide and conquer, and dynamic programming Apply powerful string matching techniques and optimize your application logic Master graph representations and learn about different graph algorithms This course is ideal for individuals who are If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the course for you. It is particularly useful for If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the course for you.

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Summary

Title: Beginning Java Data Structures and Algorithms

Price: $49.99

Average Rating: 4.5

Number of Lectures: 35

Number of Quizzes: 6

Number of Published Lectures: 35

Number of Published Quizzes: 6

Number of Curriculum Items: 41

Number of Published Curriculum Objects: 41

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Understand some of the fundamental concepts behind key algorithms

Express space and time complexities using Big O notation.

Correctly implement classic sorting algorithms such as merge and quicksort

Correctly implement basic and complex data structures

Learn about different algorithm design paradigms, such as greedy, divide and conquer, and dynamic programming

Apply powerful string matching techniques and optimize your application logic

Master graph representations and learn about different graph algorithms

Who Should Attend

If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the course for you.

Target Audiences

If you want to better understand common data structures and algorithms by following code examples in Java and improve your application efficiency, then this is the course for you.

Learning about data? structures and algorithms gives you better insight on how to solve? common programming problems. Most of the problems faced every day by? programmers have been solved, tried, and tested. By knowing how these? solutions work, you can ensure that you choose the right tool when you? face these problems.

This course teaches you tools? that you can use to build efficient applications. It starts with an? introduction to algorithms and big O notation, later explains bubble,? merge, quicksort, and other popular programming patterns. You’ll also? learn about data structures such as binary trees, hash tables, and? graphs. The course progresses to advanced concepts, such as algorithm? design paradigms and graph theory. By the end of the course, you will? know how to correctly implement common algorithms and data structures? within your applications.?

About the Author

Kristian Secor has been in? the industry for quite a while. He a M.S. focusing on web development? and an Ed.D focusing on educational technology. He has been developing? for about 20 years and has been teaching for about 16 years at the? University level for the frontend, backend, and mobile application? courses. Currently, he is working as the Program Head for the Web? Development Department at San Diego Mesa College. He is also an? instructor for both user experience and frontend development at U.C. San? Diego Extension.?

Course Curriculum

Chapter 1: Algorithms and Complexities

Lecture 1: Course Overview

Lecture 2: Lesson Overview

Lecture 3: Developing Our First Algorithm

Lecture 4: Measuring Algorithmic Complexity with Big O Notation

Lecture 5: Identifying Algorithms with Different Complexities

Lecture 6: Summary

Chapter 2: Sorting Algorithms and Fundamental Data Structures

Lecture 1: Lesson Overview

Lecture 2: Introducing Bubble Sorting

Lecture 3: Understanding Quick Sort

Lecture 4: Using Merge Sort

Lecture 5: Getting Started with Fundamental Data Structures

Lecture 6: Summary

Chapter 3: Hash Tables and Binary Search Trees

Lecture 1: Lesson Overview

Lecture 2: Introducing Hash Tables Part 1

Lecture 3: Introducing Hash Tables Part 2

Lecture 4: Getting Started with Binary Search Trees

Lecture 5: Traversing a Binary Search Tree

Lecture 6: Summary

Chapter 4: Algorithm Design Paradigms

Lecture 1: Lesson Overview

Lecture 2: Introducing Greedy Algorithms

Lecture 3: Getting Started with Divide and Conquer Algorithms

Lecture 4: Understanding Dynamic Programming

Lecture 5: Summary

Chapter 5: String Matching Algorithms

Lecture 1: Lesson Overview

Lecture 2: Naive Search Algorithms

Lecture 3: Getting Started with the Boyer-Moore String Searching Algorithm

Lecture 4: Introducing Other String Matching Algorithms

Lecture 5: Summary

Chapter 6: Graphs, Prime Numbers, and Complexity Classes

Lecture 1: Lesson Overview

Lecture 2: Representing Graphs

Lecture 3: Traversing a Graph

Lecture 4: Calculating Shortest Paths

Lecture 5: Prime Numbers in Algorithms

Lecture 6: Other Concepts in Graphs

Lecture 7: Summary

Instructors

Packt Publishing
Tech Knowledge in Motion

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Frequently Asked Questions

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