Data Structures & Algorithms in Java: Introduction

Java SE 13
  • 16 Videos | 2h 5s
  • Includes Assessment
  • Earns a Badge
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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

  • Playable
    1. 
    Course Overview
    1m 57s
    UP NEXT
  • Playable
    2. 
    Introduction to Data Structures and Algorithms
    8m 31s
  • Locked
    3. 
    Data Structures vs. Abstract Data Types
    3m 9s
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    4. 
    Dimensions of Performance
    7m 43s
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    5. 
    Complexity as a Measure of Performance
    9m 27s
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    6. 
    The Big-O Notation
    9m 33s
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    7. 
    Getting Started with a New Java Project
    3m 29s
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    8. 
    Constant Time Complexity
    10m 29s
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    9. 
    Linear Time Complexity Algorithms
    9m 48s
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    10. 
    Additional Algorithms with Linear Time Complexity
    8m 22s
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    11. 
    Timing Operations with Linear Time Complexity
    4m 33s
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    12. 
    Simple Algorithms with Linear Time Complexity
    6m 37s
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    13. 
    Quadratic Time Complexity
    6m 29s
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    14. 
    Cubic Time Complexity
    11m 19s
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    15. 
    Logarithmic Time Complexity
    9m 58s
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    16. 
    Course Summary
    1m 42s

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