LPU - Lovely Professional University
What you'll learn

This final module of the Data Structures & Algorithms with Java Bootcamp is designed to bring together everything you’ve learned throughout the program and apply it to real-world problem solving. Here, you’ll work on advanced coding challenges and hands-on projects that test your understanding of core DSA concepts using Java. From recursion and dynamic programming to trees, graphs, hashing, and backtracking, you’ll strengthen your ability to design efficient and optimized solutions for complex problems. The focus goes beyond simply finding the correct answer—you’ll learn how to write clean, scalable, and high-performance Java code that can handle real interview scenarios and practical software development challenges. This module serves as your DSA capstone experience, helping you transition from learning concepts to building complete solutions with confidence. By the end of the Data Structures & Algorithms with Java Bootcamp, you’ll be able to solve advanced DSA problems using industry-relevant techniques such as graph traversal, dynamic programming, and recursion. You’ll gain confidence in selecting the right data structures—including stacks, queues, heaps, trees, and hash maps—to solve real-world problems effectively. Most importantly, you’ll develop complete Java-based projects that demonstrate your analytical thinking, coding efficiency, and problem-solving abilities, preparing you for technical interviews and professional software development roles.

  • Introduction to Java, Object-Oriented Programming Concepts (Class, Object, Inheritance, Polymorphism, Encapsulation, Abstraction), Exception Handling, Collections Framework (ArrayList, LinkedList, HashMap, Stack, Queue), File Handling, Multithreading Basics, and Practice Programs.
  • Introduction to DSA, Time & Space Complexity, Arrays – Basics and Operations (Insert, Delete, Search), Arrays – Sorting (Bubble, Selection, Insertion), Searching (Binary Search, Two-Pointer, etc.), and Arrays – Practice Problems.
  • Linked Lists: Introduction, Memory Representation, Allocation, Traversal, Insertion, Deletion, Header Linked Lists, Two-Way Lists, and Operations on Doubly Linked Lists
  • Stacks: Introduction, List and Array Representations, Operations on Stack (Traversal, Push, Pop), Queue: Array and List Representation, Operations (Traversal, Insertion, Deletion), Circular Queue, and Priority Queue.
  • Hashing – Hash Tables, Collision Handling, Hashing Applications (Frequency Count, LRU Cache), Heaps – Min Heap, Max Heap, Heap Sort, and Practice Problems on Hashing and Heaps.
  • Tree Binary Trees – Introduction (Complete and Extended Binary Trees), Memory Representation (Linked, Sequential), Binary Search Trees – Searching, Insertion, Deletion, Traversals, and Practice Problems.

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Mukesh Sharma
Assistant Professor

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Arvind Kumar
Assistant Professor

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