Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms

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Overview
Course Content
Requirements & Materials

Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms

Course Description

This Data Structures & Algorithms course completes the data structures portion presented in the sequence of courses with self-balancing AVL and (2-4) trees. It also begins the algorithm portion in the sequence of courses as you will investigate and explore the two more complex data structures: AVL and (2-4) trees. Both of these data structures focus on self-balancing techniques that will ensure all operations are O(log n). Time complexity is threaded throughout the course within all the data structures and algorithms and a short Java review is presented on topics relevant to new data structures covered in this course. The course does require prior knowledge of Java, object-oriented programming, and linear and nonlinear data structures.

AVL TREES

(2-4) TREES

ITERATIVE SORTING ALGORITHMS

DIVIDE & CONQUER SORTING ALGORITHMS

Prerequisites

Recommended

Basic knowledge of the Java programming language, object-oriented principles, and the following abstract data types: Binary Search Trees, Heaps, and Hashmaps.

Materials

Required

Internet connection (DSL, LAN, or cable connection desirable)

COURSE ID: DL 0062M

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Who Should Attend

This course is designed for anyone who wants to learn more complex tree data structures, AVL and (2-4) trees; investigate the balancing techniques found in both tree types; implement these techniques in AVL operations; or explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. You will use the course visualizations to understand the performance.

What You Will Learn

Java programming skills by implementing AVLs and sorting algorithms
Study techniques for restoring balance in AVL and (2-4) trees
When to apply single and double rotations in AVLs
Complex (2-4) trees that exhibit underflow and overflow problems
The appropriate use of promotion, transfer, and fusion in (2-4) trees
The time complexity for the AVLs, (2-4) Trees, and sorting algorithms

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How You Will Benefit

Implement basic iterative sorting algorithms: Bubble, Insertion, and Selection.
Explore optimizations to improve efficiency, including Cocktail Shaker Sort.
Contemplate two Divide & Conquer comparison sorting algorithms Merge and Quick Sort.
Consider one non-comparison Divide & Conquer algorithm: LSD Radix Sort.
Analyze the stability, memory usage, and adaptations of all sorting algorithms presented.

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Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms