Manage Binary Trees for Java Performance

This course is part of Level Up: Java-Powered Machine Learning Specialization

Instructors: Sonali Sen Baidya

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Apply node-insertion and deletion operations in Java to maintain a Binary Search Tree.
Evaluate the time complexity of search, insertion, and deletion operations for both balanced and skewed BSTs.
Demonstrate balancing techniques (e.g., AVL rotations) to improve BST performance.

Skills you'll gain

Tools you'll learn

Tree Maps

Details to know

Shareable certificate

Add to your LinkedIn profile

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Build your subject-matter expertise

This course is part of the Level Up: Java-Powered Machine Learning Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Transform your Java development skills by mastering the secret to building high-performance, scalable applications: Binary Search Trees. This course includes comprehensive career development resources to help learners transition into software engineering and performance optimization roles. You’ll receive guidance on exploring career paths in backend engineering, systems performance engineering, and Java development. Learners will also discover how to build job-ready portfolios showcasing data structure and algorithm projects, optimize resumes with performance-tuning and Java-specific keywords, and prepare for technical interviews focused on Binary Search Trees, complexity analysis, and balancing techniques. By the end of this course, you’ll have the skills to confidently implement and optimize Binary Search Trees in Java, diagnose and prevent performance bottlenecks caused by skewed trees, and apply balancing techniques to enhance runtime efficiency and search performance.

This module introduces the fundamentals of Binary Search Trees (BSTs) and demonstrates how the structure of a tree—whether balanced or skewed—directly affects search performance in Java applications. Learners will explore BST properties, node insertion and deletion rules, and tree traversal techniques, gaining hands-on experience to understand how different insertion patterns impact tree shape and efficiency.

What's included

4 videos2 readings1 peer review

4 videos Total 39 minutes

Welcome to Binary Tree Performance 4 minutes
Fundamentals of Binary Search Trees 9 minutes
Implementing Node Insertion in Java 17 minutes
Deletion in Binary Search Trees 9 minutes

2 readings Total 15 minutes

Welcome to the Course: Course Overview 5 minutes
Binary Search Trees Explained 10 minutes

1 peer review Total 25 minutes

Hands-On-Learning: Exploring BST and its Operations Using Java 25 minutes

This module introduces learners to the performance characteristics of Binary Search Trees in Java. It emphasizes the role of tree height in determining runtime efficiency and contrasting balanced and skewed structures. Learners will explore the time complexity of search, insertion, and deletion operations, analyze performance through code benchmarks, and use visualization tools to understand how insertion patterns impact efficiency.

What's included

3 videos1 reading1 peer review

This module introduces learners to balancing techniques that maintain BST performance over time. It covers why skew occurs, how rotations restore balance, and how self-balancing trees (e.g., AVL) guarantee O(log n) operations. Learners will explore rotation algorithms, practice rebalancing skewed trees, and apply optimization strategies to ensure consistent runtime efficiency in Java applications.

What's included

4 videos1 reading1 assignment2 peer reviews

4 videos Total 36 minutes

Introduction to AVL Trees 9 minutes
Implementing Rotations in Java 14 minutes
Case Study: From Skewed to Balanced BST 10 minutes
Course Wrap-Up 4 minutes

1 reading Total 10 minutes

AVL Rotations Explained 10 minutes

1 assignment Total 20 minutes

Manage Binary Trees for Java Performance 20 minutes

2 peer reviews Total 90 minutes

Hands-On-Learning: Implementing AVL Tree Rotations for Guaranteed Performance 30 minutes
Project: The Complete Binary Search Tree Performance Challenge: From Degradation to Optimization 60 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Sonali Sen Baidya

Coursera

6 Courses 8,902 learners

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