Book Image

Beginning Java Data Structures and Algorithms

By : Kristian Secor
Book Image

Beginning Java Data Structures and Algorithms

By: Kristian Secor

Overview of this book

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.

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Beginning Java Data Structures and Algorithms
Kristian Secor
Jan, 2019 | 2 hours 56 minutes
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Table of Contents (6 chapters)
Free Chapter
1
Algorithms and Complexities
Course Overview
Lesson Overview
Developing Our First Algorithm
Measuring Algorithmic Complexity with Big O Notation
Identifying Algorithms with Different Complexities
Summary
2
Sorting Algorithms and Fundamental Data Structures
Lesson Overview
Introducing Bubble Sorting
Understanding Quick Sort
Using Merge Sort
Getting Started with Fundamental Data Structures
Summary
3
Hash Tables and Binary Search Trees
Lesson Overview
Introducing Hash Tables Part 1
Introducing Hash Tables Part 2
Getting Started with Binary Search Trees
Traversing a Binary Search Tree
Summary
4
Algorithm Design Paradigms
Lesson Overview
Introducing Greedy Algorithms
Getting Started with Divide and Conquer Algorithms
Understanding Dynamic Programming
Summary
5
String Matching Algorithms
Lesson Overview
Naive Search Algorithms
Getting Started with the Boyer-Moore String Searching Algorithm
Introducing Other String Matching Algorithms
Summary
6
Graphs, Prime Numbers, and Complexity Classes
Lesson Overview
Representing Graphs
Traversing a Graph
Calculating Shortest Paths
Prime Numbers in Algorithms
Other Concepts in Graphs
Summary
Chapter 1
Algorithms and Complexities
Content Locked
Section 4
Measuring Algorithmic Complexity with Big O Notation
Algorithmic complexity is a way to describe the efficiency of an algorithm as a relation of its input. It can be used to describe various properties of our code, such as runtime speed or memory requirements. It's also a very important tool programmers should understand to write efficient software. In this topic, we will start by describing a scenario, introducing the topic, and then dive into the details of the various types of complexities and the different techniques to measure them.
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End of Section 4
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