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

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. Explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. Use the course visualizations to understand the performance.

Data Structures & Algorithms Course

Course Description

This Data Structures & Algorithms course is an intermediate-level offering from GTx that builds upon foundational knowledge of Java programming and linear and nonlinear data structures. The course delves deep into advanced data structures like AVL and (2-4) trees, and introduces a variety of sorting algorithms, from basic iterative methods to more complex divide-and-conquer approaches. Throughout the course, there's a strong emphasis on time complexity analysis, ensuring students develop a keen understanding of algorithmic efficiency.

What students will learn

Advanced data structures: AVL and (2-4) trees
Self-balancing techniques for tree structures
Various sorting algorithms: Bubble, Selection, Insertion, Merge, Quick, and LSD Radix sort
Time complexity analysis for all covered data structures and algorithms
Optimization techniques for sorting algorithms
Implementation of data structures and algorithms in Java
Analysis of algorithm stability, memory usage, and adaptiveness

Prerequisites

Basic knowledge of Java programming language
Understanding of object-oriented programming principles
Familiarity with abstract data types: Binary Search Trees, Heaps, and Hashmaps
Prior knowledge of linear and nonlinear data structures

Course Coverage

AVL Trees: properties, self-balancing techniques, and rotations
(2-4) Trees: structure, operations, and handling overflow/underflow situations
Iterative sorting algorithms: Bubble, Selection, Insertion, and Cocktail Shaker sort
Divide & Conquer sorting algorithms: Merge and Quick sort
Non-comparison sorting: LSD Radix sort
Time complexity analysis for all covered topics
Java implementation of data structures and algorithms

Target Audience

This course is ideal for computer science students, software developers, and programming enthusiasts who want to deepen their understanding of advanced data structures and algorithms. It's particularly suitable for those looking to improve their problem-solving skills, optimize code efficiency, and prepare for technical interviews in the software industry.

Real-world Application

Develop more efficient software applications
Optimize database operations and search algorithms
Improve performance in large-scale systems and applications
Enhance problem-solving skills for complex computational challenges
Excel in technical interviews for software engineering positions
Contribute to open-source projects requiring advanced data structure knowledge
Analyze and improve existing algorithms in various domains

Syllabus

Module 0: Introduction and Review

Module 8: AVL Trees

Module 9: (2-4) Trees

Module 10: Iterative Sorting Algorithms

Module 11: Divide & Conquer Sorting Algorithms

Each module consists of short instructional videos, textual content, exploratory labs with visualization tools, comprehension questions, and Java coding assignments. The course concludes with a final exam. Grading is based on comprehension questions (10%), coding assignments (60%), and the final exam (30%).