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Il y a 3 modules dans ce cours
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.
Inclus
4 vidéos2 lectures1 évaluation par les pairs
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4 vidéos•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 lectures•Total 15 minutes
Welcome to the Course: Course Overview•5 minutes
Binary Search Trees Explained•10 minutes
1 évaluation par les pairs•Total 25 minutes
Hands-On-Learning: Exploring BST and its Operations Using Java •25 minutes
Analyzing BST Performance and Time Complexity
Module 2•1 heure à terminer
Détails du module
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.
Inclus
3 vidéos1 lecture1 évaluation par les pairs
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3 vidéos•Total 44 minutes
Time Complexity of BST Operations•9 minutes
Measuring Performance in Java BSTs•19 minutes
Visualizing Complexity with BST Examples•16 minutes
1 lecture•Total 10 minutes
Balanced vs Skewed BST Performance•10 minutes
1 évaluation par les pairs•Total 25 minutes
Hands-On-Learning: Measuring and Comparing BST Performance Across Tree Structures •25 minutes
Balancing and Optimizing Binary Search Trees
Module 3•3 heures à terminer
Détails du module
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.
Inclus
4 vidéos1 lecture1 devoir2 évaluations par les pairs
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4 vidéos•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 lecture•Total 10 minutes
AVL Rotations Explained•10 minutes
1 devoir•Total 20 minutes
Manage Binary Trees for Java Performance•20 minutes
2 évaluations par les pairs•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
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