Name: Java DSA: LEETCODE Exercises — Trees & Graphs
Availability: InStock

Java DSA: LEETCODE Exercises — Trees & Graphs – a hands‑on Udemy course by Interview Practice Academy. Updated July 2026, this free Java course teaches non‑linear data structures, advanced graph algorithms, and interview‑ready coding patterns. Learners gain practical skills to solve high‑frequency LeetCode problems, earn a Udemy certificate, and boost their chances of landing a FAANG/MAANG role.

What You'll Learn

Build custom tree and graph representations in Java using adjacency lists, matrices, and standard library nodes.
Master recursive and iterative traversals—In‑Order, Pre‑Order, Post‑Order, and Level‑Order—on binary trees and graphs.
Learn insertion, deletion, search, validation, and balancing techniques for Binary Search Trees (BSTs) with optimal time complexity.
Understand when to apply Depth‑First Search versus Breadth‑First Search for reachability and path‑finding challenges.
Create Dijkstra’s, Bellman‑Ford, Prim’s, and Kruskal’s algorithms with Java’s PriorityQueue for shortest‑path and MST problems.
Implement Disjoint Set Union (Union‑Find) with path compression and union‑by‑rank for dynamic connectivity.
Apply Trie structures for prefix matching, autocomplete, and high‑performance dictionary searches.
Analyze dynamic‑programming solutions on trees, including diameter, maximum path sum, and subtree subproblems.

Course Details

Instructor: Interview Practice Academy
Enrolled students: 41,322
Language: English (en‑US)
Certificate: Yes, upon completion
Includes: Lifetime access, mobile‑friendly videos, self‑paced learning

What This Course Covers

Tree Fundamentals

Binary Tree node design, null‑safety, and pointer manipulation in Java.
Recursive and iterative implementations of In‑Order, Pre‑Order, Post‑Order, and Level‑Order traversals.
Binary Search Tree (BST) insertion, deletion, search, and validation with O(log n) complexity.
Lowest Common Ancestor (LCA) queries and balanced tree rotations for AVL trees.

Advanced Tree Techniques

Trie (Prefix Tree) construction for auto‑complete and dictionary lookups.
Segment Tree and Binary Heap implementations for range queries and priority queues.
Tree serialization/deserialization strategies for persistent storage.
Dynamic programming on trees: diameter calculation, maximum path sum, and subtree DP patterns.

Graph Foundations

Graph representation choices: adjacency matrix, adjacency list, and edge list.
Directed vs. undirected graph properties, self‑loops, and multigraph handling.
Basic DFS and BFS traversals using Java’s Stack and Queue collections.
Cycle detection methods for both directed and undirected graphs.

Graph Algorithms

Topological Sort using Kahn’s algorithm and DFS‑based ordering.
Shortest‑path algorithms: Dijkstra’s with PriorityQueue, Bellman‑Ford for negative edges.
Minimum Spanning Tree (MST) techniques: Prim’s (priority queue) and Kruskal’s (Union‑Find).
Strongly Connected Components via Kosaraju’s and Tarjan’s algorithms.

Optimization & Real‑World Applications

Time and space complexity evaluation for recursive call stacks and iterative loops.
Path compression and union‑by‑rank to accelerate Disjoint Set Union operations.
Memory‑efficient graph modeling for large‑scale networks and social graphs.
Translating interview problems into production‑grade Java code with clean OOP practices.

Interview Strategy & Practice

Pattern‑recognition checklist for common Tree and Graph LeetCode questions.
Step‑by‑step walkthroughs from brute‑force to optimal solutions.
Edge‑case handling for empty trees, single‑node graphs, and cyclic paths.
Tips for articulating algorithmic trade‑offs during live coding assessments.

Who Should Take This Course

Software engineers seeking deeper mastery of non‑linear data structures in Java.
Computer science students preparing for campus placements or algorithm‑heavy coursework.
Tech interview candidates targeting FAANG/MAANG coding rounds that emphasize trees and graphs.
Backend Java developers who need to optimize low‑level data handling within Spring Boot or similar frameworks.
Competitive programmers aiming to improve speed and accuracy on graph‑centric challenges.

Prerequisites

Basic proficiency in Java syntax, object‑oriented concepts, and standard collections.
Familiarity with elementary data structures such as arrays and linked lists is helpful but not mandatory.
No prior experience with trees or graphs required; the course is designed to bring beginners to an advanced level.

Why Enroll in This Course

Enroll now to claim a free coupon that grants 100 % off for a limited time. The offer expires soon, making the course effectively free for a short window. Compared with other Udemy tutorials, this training focuses exclusively on LeetCode‑style Tree and Graph problems, providing concrete code, complexity analysis, and interview tactics. The combination of AI‑assisted explanations and hands‑on Java exercises ensures rapid skill acquisition without unnecessary fluff.

Course Highlights

Lifetime access to all video lectures, code files, and practice exercises.
Mobile‑friendly content lets learners code and review concepts on any device.
Certificate of completion adds credibility to LinkedIn profiles and résumés.
Self‑paced format accommodates full‑time professionals and students alike.
AI‑enhanced explanations deliver adaptive insights into complex algorithmic patterns.
30‑day money‑back guarantee provides risk‑free enrollment for peace of mind.

Frequently Asked Questions

Q: Is this course really free?
A: Yes, the course can be accessed at no cost while the free coupon remains active. The 100 % discount applies automatically at checkout, removing any payment requirement.

Q: What will I learn in this Java DSA course?
A: You will learn to build custom tree and graph structures, execute recursive and iterative traversals, implement shortest‑path and MST algorithms, and solve advanced LeetCode problems using clean Java code. Each module includes detailed complexity analysis and real‑world use cases.

Q: Do I get a certificate after completing this course?
A: A Udemy certificate of completion is awarded once all lectures and exercises are finished. The certificate can be shared on professional networks to demonstrate your new expertise.

**Q: Is this course suitable for