Data Structures for Coding Interviews in Java

This course provides a complete discussion of code implementation and prepares the developers for interview questions on data structures in Java.

Beginner

230 Lessons

35h

Certificate of Completion

This course provides a complete discussion of code implementation and prepares the developers for interview questions on data structures in Java.

AI-POWERED

Code Feedback

Mock Interview

Explanations

AI-POWERED

Code Feedback

Mock Interview

This course includes

153 Playgrounds

65 Challenges

22 Quizzes

This course includes

153 Playgrounds

65 Challenges

22 Quizzes

Course Overview

Data structures are amongst the fundamentals of Computer Science and an important decision in every program. Consequently, they are also largely categorized as a vital benchmark of computer science knowledge when it comes to industry interviews. This course contains a detailed review of all the common data structures and provides implementation level details in Java to allow readers to become well equipped. Now with more code solutions, lessons, and illustrations than ever, this is the course for you!

TAKEAWAY SKILLS

Programming Language

Java

Prepare For Interview

Data Structures

Time Complexity

Course Content

Complexity Measures

This chapter covers time and space complexity, Big O notation, and analyzing nested loops with various challenges to understand algorithm efficiency.

Comparing Algorithms Example: Measuring Time Complexity of a Single Loop Algorithm Example: Time Complexity of an Algorithm With Nested Loops

Complexity Interview Questions

Arrays

In this chapter, you will explore array operations, including merging, rotating, and finding values with practical challenges and solutions in Java.

What is an Array?

Two Dimensional Arrays What Is a List?

Challenge: Remove Even Integers From Array Solution: Remove Even Integers From Array Challenge: Merge Two Sorted Arrays Solution: Merge Two Sorted Arrays Challenge: Find Two Numbers That Add Up to K Solution: Find Two Numbers That Add Up to K Challenge: Product of Array Except Self Solution: Product of Array Except Self Challenge: Find Minimum Value in Array Solution: Find Minimum Value in Array Challenge: First Non-Repeating Integer in an Array Solution: First Non-Repeating Integer in an Array Challenge: Find Second Maximum Value in an Array Solution: Find Second Maximum Value in an Array Challenge: Rotate Array Solution: Rotate Array Challenge: Rearrange Positive & Negative Values Solution: Rearrange Positive & Negative Values Challenge: Rearrange Sorted Array in Max/Min Form Solution: Rearrange Sorted Array in Max/Min Form Challenge: Maximum Subarray Solution: Maximum Subarray Array Interview Questions

Linked Lists

This chapter discusses linked lists, including singly and doubly linked lists, with challenges related to insertion, deletion, and finding elements.

What is the Singly Linked List (SLL)?Basic Linked List Operations Insertion in a Singly Linked List Insertion in Singly Linked List (Insert After)Singly Linked List Deletion (Implementation)Linked Lists vs. Arrays What is a Doubly Linked List (DLL)?Linked List with Tail Challenge: Insertion at Tail Solution: Insertion at Tail Challenge: Search in a Singly Linked List Solution: Search in a Singly Linked List Challenge: Deletion by Value Solution: Deletion by Value Challenge: Find the Length of a Linked List Solution: Find the Length of a Linked List

Challenge: Reverse Linked List Solution: Reverse Linked List Challenge: Linked List Cycle Solution: Linked List Cycle Challenge: Middle of the Linked List Solution: Middle of the Linked List Challenge: Remove Duplicates from a Linked List Solution: Remove Duplicates from a Linked List Challenge: Union and Intersection of Linked Lists Solution: Union and Intersection of Linked Lists Challenge: Return the Nth Node from End Solution: Return the Nth Node from End Challenge: Find If a Doubly Linked List Is a Palindrome Solution: Find If a Doubly Linked List Is a Palindrome Linked list Interview Questions

Stack/Queues

This chapter covers stacks and queues, their implementations, and practical challenges like binary number generation and parenthesis validation.

What is a Stack?Stack (Implementation)What is a Queue?Queue (Implementation)

Challenge: Generate Binary Numbers From 1 to n Using a Queue Solution: Generate Binary Numbers From 1 to n Using a Queue Challenge: Implement Two Stacks Using One Array Solution: Implement Two Stacks Using One Array

Challenge: Reverse First k Elements of Queue Solution: Reverse First k Elements of Queue

Challenge: Implement Queue Using Stacks Solution: Implement Queue Using Stacks Challenge: Sort Values in a Stack Solution: Sort Values in a Stack Challenge: Evaluate Postfix Expression Using a Stack Solution: Evaluate Postfix Expression Using a Stack Challenge: Next Greater Element Using a Stack Solution: Next Greater Element Using a Stack Challenge: Find the Celebrity Solution: Find the Celebrity Challenge: Valid Parentheses Solution: Valid Parentheses Challenge: Min Stack Solution: Min Stack Stack/Queue Interview Questions

Graphs

In this chapter, you will learn about graph representation, traversal algorithms like BFS and DFS, and challenges such as cycle detection and shortest path.

What is a Graph?

Representation of Graphs

Graph Implementation Complexities of Graph Operations What is a Bipartite Graph?Graph Traversal Algorithms Challenge: Implement Breadth-First Search Solution: Implement Breadth-First Search Challenge: Implement Depth-First Search Solution: Implement Depth-First Search Challenge: Detect Cycle in a Directed Graph Solution: Detect Cycle in a Directed Graph Challenge: Find a Mother Vertex in a Directed Graph Solution: Find a Mother Vertex in a Directed Graph Challenge: Count the Number of Edges in an Undirected Graph Solution: Count the Number of Edges in an Undirected Graph Challenge: Check If a Path Exists between Two Vertices Solution: Check If a Path Exists between Two Vertices Challenge: Graph Valid Tree Solution: Graph Valid Tree Challenge: Find the Shortest Path between Two Vertices Solution: Find the Shortest Path between Two Vertices Challenge: Remove Edge from a Directed Graph Solution: Remove Edge from a Directed Graph Graph Interview Questions

Trees

38 Lessons

This chapter introduces various trees, including binary, AVL, and red-black trees, with challenges on insertion, deletion, and traversal techniques.

Trie (Advanced Trees)

14 Lessons

This chapter explores Tries for string operations, including insertion, search, and deletion, with challenges on word formation and sorting.

Heaps

14 Lessons

In this chapter, you will understand heaps, focusing on max and min heaps, and solve challenges related to converting heaps and finding elements.

Hash Tables

33 Lessons

This chapter covers hash tables, including hash functions, collision handling, and practical challenges like subset checks and word formation.

10.

Summary of Data Structures

2 Lessons

This chapter provides an overview of linear and non-linear data structures, summarizing their differences and concluding with course recommendations.

Course Author

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Part of the Java Interview Prep Path

Ace the Java Coding Interview

Learn to tackle anything you might face in a coding interview in Java with absolute confidence.

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Software Developer

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Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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Frequently Asked Questions

Which data structure should be used in Java?

In Java, the choice of data structure depends on the specific use case:

Array: Use when you need fast access by index and the collection size is fixed.
ArrayList: Use for dynamic arrays when you frequently access elements by index and occasionally add or remove elements.
LinkedList: Use when you need frequent insertions and deletions, especially at the beginning or middle of the list.
HashMap: Use for key-value pairs when you need fast lookups, insertions, and deletions based on keys.
HashSet: Use to store unique elements with no duplicates and when order does not matter.
TreeMap: Use when you need key-value pairs sorted by their keys.
Stack: Use for last in, first out (LIFO) operations.
Queue: Use for first in, first out (FIFO) operations.
PriorityQueue: Use when you need elements sorted or retrieved by priority.

Choose the data structure that best matches your performance requirements for the specific operations you need.

Is Java a good choice for coding interviews?

Yes, Java is an excellent choice for coding interviews. Many companies accept and favor it because of its clear syntax, making code easy to read and understand. Java’s strong typing catches errors at compile-time, which can help ensure your solution is robust and error-free. Additionally, Java offers a rich standard library (java.util), which provides efficient data structures and utility functions to implement common algorithms quickly. Its performance is also reliable, making it suitable for handling time-sensitive problems. Given its popularity and versatility, Java is a solid choice for technical interviews.

How to crack a Java coding interview

To crack a Java coding interview, master core Java concepts like object-oriented programming (OOP), exception handling, collections framework, and multithreading. Practice solving common algorithmic problems using Java’s data structures, such as ArrayList, HashMap, and TreeSet, while understanding their time complexities. Get comfortable writing clean, efficient code and explaining your thought process clearly. Familiarize yourself with Java’s syntax, best practices, and nuances. Review design patterns, JVM internals, and Java-specific features that may be relevant to the role you’re interviewing for. Regularly practice mock interviews to build confidence and improve your problem-solving speed.

Is Java coding difficult?

Java coding is not inherently difficult, but it does have a learning curve, especially for beginners. Its syntax is relatively straightforward and readable, and its object-oriented nature helps organize code efficiently. However, mastering Java involves understanding various concepts like data structures, algorithms, exception handling, concurrency, and knowing its extensive standard library. Java becomes easier with consistent practice and a solid grasp of programming fundamentals. The key is building a strong foundation and practicing to become proficient.

Is Java faster than C++?

Java is generally slower than C++ because Java is an interpreted language that runs on the Java virtual machine (JVM), which adds an extra layer of abstraction and overhead. In contrast, C++ is a compiled language that translates directly into machine code, resulting in faster execution. However, Java’s just-in-time (JIT) compiler optimizes code at runtime, narrowing the performance gap in many cases. Ultimately, C++ is often chosen for performance-critical applications, while Java offers better portability and ease of use.