Coursera

Manage Binary Trees for Java Performance

Coursera

Manage Binary Trees for Java Performance

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

Sonali Sen Baidya
Starweaver

Instructors: Sonali Sen Baidya

Access provided by DBS Bank

Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
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.

Details to know

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Assessments

1 assignment

Taught in English
Recently updated!

January 2026

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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

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

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

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Instructors

Sonali Sen Baidya
Coursera
6 Courses 8,515 learners

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