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Overview
MindTap for Azevedo/Cutajar's Java Data Structures, 1st Edition is the digital learning solution that powers students from memorization to mastery. This course teaches students how to write systematic code in Java and improve application efficiency with hands-on practice, step-by-step instruction, and provides immediate feedback and troubleshooting support on their code. Students will develop skills that are in-demand by employers by completing authentic, real-world coding projects that can be added to their GitHub portfolios.
Module 1:
Algorithms and Complexities:
Developing Our First Algorithm.
Measuring Algorithmic Complexity with Big O Notation.
Identifying Algorithms with Different Complexities.
Module 2:
Sorting Algorithms and Fundamental Data Structures:
Introducing Bubble Sorting.
Understanding Quick Sort.
Using Merge Sort.
Getting Started with Fundamental Data Structure.
Module 3:
Hash Tables and Binary Search Tree:
Introducing Hash Tables.
Getting Started with Binary Search Trees.
Module 4:
Algorithm Design Paradigms:
Introducing Greedy Algorithms.
Getting Started with Divide and Conquer Algorithms.
Understanding Dynamic Programming.
Module 5:
String Matching Algorithms:
Naive Search Algorithms.
Getting Started with the Boyer-Moore String.
Searching Algorithms.
Introducing Other String Matching Algorithms.
Module 6:
Graphs, Prime Numbers, and Complexity Classes:
Representing Graphs.
Traversing A Graph.
Calculating Shortest Paths.
Prime Numbers in Algorithms.
Other Concepts in Graphs.
Understanding Complexity Classes of Problems.
Algorithms and Complexities:
Developing Our First Algorithm.
Measuring Algorithmic Complexity with Big O Notation.
Identifying Algorithms with Different Complexities.
Module 2:
Sorting Algorithms and Fundamental Data Structures:
Introducing Bubble Sorting.
Understanding Quick Sort.
Using Merge Sort.
Getting Started with Fundamental Data Structure.
Module 3:
Hash Tables and Binary Search Tree:
Introducing Hash Tables.
Getting Started with Binary Search Trees.
Module 4:
Algorithm Design Paradigms:
Introducing Greedy Algorithms.
Getting Started with Divide and Conquer Algorithms.
Understanding Dynamic Programming.
Module 5:
String Matching Algorithms:
Naive Search Algorithms.
Getting Started with the Boyer-Moore String.
Searching Algorithms.
Introducing Other String Matching Algorithms.
Module 6:
Graphs, Prime Numbers, and Complexity Classes:
Representing Graphs.
Traversing A Graph.
Calculating Shortest Paths.
Prime Numbers in Algorithms.
Other Concepts in Graphs.
Understanding Complexity Classes of Problems.