# Data Structures & Algorithms in Java: Introduction

Java SE 13    |    Beginner
• 16 Videos | 2h 5s
• Includes Assessment
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Refine your programming skills by exploring the most commonly-used data structures and algorithms in Java. In this course, you'll learn about the importance of data structures and algorithms in writing efficient and correct code. You'll explore the differences between abstract data types and data structures. You'll then learn how you can use complexity to measure the performance of your code based on running time, space, network usage, and other resources. Next, you'll examine the big-O notation to measure complexity. Finally, you'll learn how to analyze different methods to determine their running time, expressed using the big-O notation.

## WHAT YOU WILL LEARN

• discover the key concepts covered in this course recall the importance of using data structures and algorithms recognize the differences between data structures and abstract data types measure performance based on time, space, and network bandwidth usage apply complexity to measure performance use the big-O notation as a measure of complexity set up a new Java project analyze algorithms with constant time complexity
• analyze algorithms with linear time complexity recognize more algorithms that have linear time complexity time operations to see how the running time changes based on input size recognize simple examples from the real world that exhibit linear time complexity analyze algorithms with quadratic time complexity analyze algorithms with cubic time complexity analyze algorithms with logarithmic time complexity summarize the key concepts covered in this course

## IN THIS COURSE

• 1.
Course Overview
• 2.
Introduction to Data Structures and Algorithms
• 3.
Data Structures vs. Abstract Data Types
• 4.
Dimensions of Performance
• 5.
Complexity as a Measure of Performance
• 6.
The Big-O Notation
• 7.
Getting Started with a New Java Project
• 8.
Constant Time Complexity
• 9.
Linear Time Complexity Algorithms
• 10.
Additional Algorithms with Linear Time Complexity
• 11.
Timing Operations with Linear Time Complexity
• 12.
Simple Algorithms with Linear Time Complexity
• 13.