Advertisements

Java DSA: LEETCODE Exercises — Trees & Graphs

Name: Java DSA: LEETCODE Exercises — Trees & Graphs
Availability: InStock
Rating: 1 (93 reviews)
Author: Jitendra Suryavanshi

Advertisements

Java DSA: LEETCODE Exercises — Trees & Graphs (Solution Code with Detailed Explanations) | Coding Practice Exercises

 1/5

(93) Ratings

0 students

Development

Created by Jitendra Suryavanshi

Advertisements

What you'll learn

Build custom Tree and Graph representations from scratch using Java’s standard libraries, standard reference nodes, adjacency lists, and matrices.
Execute In-Order, Pre-Order, Post-Order, and Level-Order traversals using both clean recursive logic and explicit stack/queue iterations.
Perform insertion, deletion, searching, validation, and balancing operations on Binary Search Trees (BSTs) with optimal time efficiency.
Evaluate time and space complexity for recursive algorithms, factoring in call-stack memory depth and space trade-offs.
Identify when to apply Depth-First Search (DFS) versus Breadth-First Search (BFS) to solve reachability, pathfinding, and level-based search problems.
Detect cycles in directed/undirected graphs and implement Topological Sort using Kahn’s Algorithm and DFS-based approaches.
Implement Dijkstra’s Algorithm, Bellman-Ford, and Minimum Spanning Tree algorithms (Prim’s and Kruskal’s) using Java’s PriorityQueue.
Build Disjoint Set Union (DSU) algorithms with Path Compression and Union by Rank to handle dynamic connectivity problems efficiently.
Construct Trie data structures to implement prefix matching, auto-complete features, and high-performance dictionary search routines.
Formulate dynamic programming solutions on hierarchical tree structures, such as tree diameter, maximum path sums, and subtree subproblems.
Handle critical edge cases seamlessly, including empty trees, single-node graphs, cyclic paths, self-loops, and memory pointers in Java.
Recognize recurring non-linear patterns within unseen technical interview questions and translate them into clean, idiomatic Java code.

This course includes:

40 total mins on-demand video

0 articles

0 downloadable resources

10 lessons

Full lifetime access

Access on mobile and TV

Certificate of completion

Advertisements

Course content

Requirements

Basic Java Syntax & Object-Oriented Fundamentals: You should be comfortable with core Java syntax (loops, conditionals, methods), standard data structures (List, Map, Set), and basic OOP concepts (classes, references, and null checks). No advanced framework experience is required.
A Development Environment (IDE): A working installation of Java Development Kit (JDK 11 or higher) along with any modern Java IDE, such as IntelliJ IDEA, Eclipse, or Visual Studio Code, to run and debug the exercise solutions.

Description

Post Views: 3

This course contains the use of artificial intelligence.

Master modern non-linear data structures and algorithmic decision-making with hands-on Java practice.

Java DSA: LEETCODE Exercises — Trees & Graphs

Prepare to crack high-paying technical interviews and level up your problem-solving skills with this targeted, non-linear data structures course. Built specifically for software engineers, computer science students, and tech professionals, this course focuses on the most frequently asked, high-yielding Tree and Graph patterns required by top-tier tech companies.

Whether you are preparing for FAANG/MAANG coding rounds, competitive programming contests, or technical assessments, this course bridges the gap between basic recursive thinking and advanced topological logic. Every exercise includes a clear breakdown of the intuition, robust Java code using the Java Collections Framework, and deep dives into time and space complexity.

Unlike theoretical lectures, this course emphasizes learning by doing. You won’t just memorize solutions—you will learn how to model real-world networks, identify traversal patterns, optimize recursive calls, and tackle complex hierarchical data structures.

What You’ll Learn

Master LeetCode-Style Problems: Solve essential Tree and Graph questions using clean, idiomatic Java (ArrayList, ArrayDeque, HashMap, PriorityQueue).
Identify Structural Patterns: Recognize when to apply Depth-First Search (DFS), Breadth-First Search (BFS), Dynamic Programming on Trees, and Disjoint Set Union (DSU).
Write Production-Grade Java Code: Focus on object-oriented representations, null-safety, pointer manipulation, and memory management in Java.
Master Complex Traversals: Implement iterative and recursive traversals, level-order processing, and path-finding algorithms with confidence.
Think Like an Interviewer: Learn how to analyze call-stack overhead, spot hidden edge cases, and articulate optimal trade-offs during live coding assessments.

Topics Covered

Trees & Hierarchical Structures

Binary Trees & BSTs: Pre-order, In-order, Post-order, Level-Order Traversal, Lowest Common Ancestor (LCA), Binary Search Tree Operations.
Balanced & Specialized Trees: AVL Trees, Tries (Prefix Trees), Segment Trees, Binary Heaps / Priority Queues.
Advanced Tree Mechanics: Tree Serialization/Deserialization, Dynamic Programming on Trees, Diameter & Path Sum Problems.

Graphs & Network Algorithms

Representations & Fundamentals: Adjacency Matrix, Adjacency List, Edge List, Directed vs. Undirected Graphs.
Graph Traversals: DFS vs. BFS, Topological Sort (Kahn’s Algorithm & DFS), Cycle Detection (Directed & Undirected).
Shortest Path & MST: Dijkstra’s Algorithm, Bellman-Ford, Prim’s & Kruskal’s Algorithms for Minimum Spanning Trees (MST).
Advanced Graph Concepts: Union-Find / Disjoint Set Union (DSU) with Path Compression, Strongly Connected Components (Kosaraju’s/Tarjan’s), Bipartite Graphs.

Course Features

Targeted LeetCode-Style Exercises: Curated, high-yield tree and graph problems directly sourced from modern tech interviews.
Complete Java Implementations: Clean, fully commented code utilizing robust Java standard library primitives and collections.
Dual Focus: Master foundational recursive thinking along with advanced network and graph algorithms.
Step-by-Step Walkthroughs: Go from initial brute-force strategies to memory-optimized, optimal solutions.
Self-Paced & Practical: Flexible, hands-on structure designed for maximum learning retention.

Why Take This Course?

Trees and Graphs form the backbone of modern software architecture—from DOM manipulation and routing networks to social graphs and recommendation engines. Consequently, tech interviewers rely heavily on these topics to test an engineer’s ability to handle complex pointer manipulation, recursion, and graph-based modeling.

This course gives you the precise strategies, code patterns, and structural intuition required to tackle non-linear problems effortlessly. Build your confidence, master complex data structures in Java, and secure your next engineering role!

Courze

Who this course is for:

Software Engineers & Developers: Developers looking to strengthen their foundational knowledge of non-linear data structures, master complex recursive thinking, and write clean, efficient Java code.
Computer Science Students & Graduates: Students preparing for campus placements, technical assessments, or upcoming data structures and algorithms coursework who want a practical, problem-first approach.
Tech Interview Candidates: Job seekers actively targeting product-based, high-paying tech companies (FAANG/MAANG) who need to master high-frequency Tree and Graph LeetCode patterns.
Self-Taught Programmers & Bootcamp Graduates: Developers transition-focused into backend or software engineering roles who have basic Java knowledge but lack structured training in advanced data structures.
Backend Java Engineers: Professionals working with enterprise Java frameworks (e.g., Spring Boot) who want to sharpen their low-level algorithmic efficiency and memory management skills.
Competitive Programmers: Coders looking to refine their speed and accuracy in solving graph and tree problems, topologically sorted dependencies, and shortest-path algorithm challenges.
Full-Stack Developers: Engineers looking to deepen their computer science fundamentals to transition smoothly into core backend, distributed systems, or infrastructure engineering roles.
Career Switchers in Tech: Professionals making a lateral move into software engineering who want a targeted, structured pathway to conquer technical coding interviews without fluff.
Engineering Managers & Tech Leads: Technical leaders re-entering the IC (Individual Contributor) job market who need a fast, high-yield refresher on non-linear coding problems in Java.