Data Structures & Algorithms in Java: Introduction

Java    |    Beginner
  • 16 videos | 1h 53m 5s
  • Includes Assessment
  • Earns a Badge
Rating 4.5 of 100 users Rating 4.5 of 100 users (100)
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

  • 1m 57s
  • 8m 31s
    After completing this video, you will be able to recall the importance of using data structures and algorithms. FREE ACCESS
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    3.  Data Structures vs. Abstract Data Types
    3m 9s
    Upon completion of this video, you will be able to recognize the differences between data structures and abstract data types. FREE ACCESS
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    4.  Dimensions of Performance
    7m 43s
    In this video, you will measure performance based on time, space, and network bandwidth usage. FREE ACCESS
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    5.  Complexity as a Measure of Performance
    9m 27s
    Find out how to apply complexity measures to performance. FREE ACCESS
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    6.  The Big-O Notation
    9m 33s
    In this video, you will use the big-O notation to measure complexity. FREE ACCESS
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    7.  Getting Started with a New Java Project
    3m 29s
    During this video, you will learn how to set up a new Java project. FREE ACCESS
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    8.  Constant Time Complexity
    10m 29s
    Learn how to analyze algorithms with a constant time complexity. FREE ACCESS
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    9.  Linear Time Complexity Algorithms
    9m 48s
    In this video, you will learn how to analyze algorithms with linear time complexity. FREE ACCESS
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    10.  Additional Algorithms with Linear Time Complexity
    8m 22s
    Upon completion of this video, you will be able to recognize more algorithms that have a linear time complexity. FREE ACCESS
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    11.  Timing Operations with Linear Time Complexity
    4m 33s
    In this video, you will time operations to see how the running time changes based on the size of the input. FREE ACCESS
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    12.  Simple Algorithms with Linear Time Complexity
    6m 37s
    After completing this video, you will be able to recognize simple examples from the real world that exhibit linear time complexity. FREE ACCESS
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    13.  Quadratic Time Complexity
    6m 29s
    During this video, you will learn how to analyze algorithms with time complexity of O(n^2). FREE ACCESS
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    14.  Cubic Time Complexity
    11m 19s
    In this video, you will analyze algorithms with time complexity of a cube. FREE ACCESS
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    15.  Logarithmic Time Complexity
    9m 58s
    In this video, find out how to analyze algorithms with a logarithmic time complexity. FREE ACCESS
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    16.  Course Summary
    1m 42s

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