Stack overflow errors crash 95% of Java applications processing deep hierarchical data, making recursive algorithm choice more critical than coding elegance. This comprehensive course equips Java developers with essential skills to build production-ready tree processing systems that handle enterprise-scale datasets without memory failures. You'll master recursive thinking patterns while developing systematic techniques to convert memory-consuming recursive algorithms into stack-safe iterative solutions using explicit data structures. You'll architect hybrid frameworks that automatically select optimal approaches based on dataset size, JVM configuration, and performance requirements. Interactive coding exercises simulate production scenarios, including debugging stack overflow crashes, optimizing memory usage for millions of nodes, and implementing fail-safe algorithms under enterprise constraints.
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What you'll learn
Configure CI/CD pipelines, jobs, and runners to automate and manage the build, test, and deploy stages of a DevOps development cycle.
Design GitLab pipeline workflows that streamline application builds, automate testing, and improve code quality and security.
Evaluate and compare deployment strategies to determine the most effective approach for different types of applications and environments.
Skills you'll gain
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December 2025
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There are 3 modules in this course
This module establishes the foundation for recursive problem-solving by teaching learners to implement and visualize core binary tree traversal algorithms from scratch in Java. Students will master the critical skills of recursive thinking patterns, call stack tracing, and building reusable TreeNode data structures while developing the ability to process hierarchical datasets containing thousands of nodes and understand when recursive solutions are optimal for tree-based problems.
What's included
4 videos2 readings1 peer review
This module develops systematic refactoring expertise by teaching learners to transform memory-consuming recursive tree algorithms into production-ready iterative solutions using explicit data structures. Students will master the critical skills of Stack and Queue-based algorithm conversion, performance optimization techniques, and memory-efficient processing patterns while enabling their applications to handle enterprise-scale datasets exceeding 50K nodes without stack overflow failures.
What's included
3 videos1 reading1 peer review
This module builds production-ready tree processing capabilities by teaching learners to implement stack-overflow detection strategies and hybrid recursive-iterative approaches for complex algorithms. Students will master the critical skills of performance analysis, algorithm selection frameworks, and enterprise-scale optimization techniques while developing the expertise to architect scalable solutions for real-world hierarchical data challenges in high-performance Java applications processing millions of records.
What's included
4 videos1 reading1 assignment2 peer reviews
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