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Data Structures for Coding Interviews in Java

The ultimate guide to data structures for coding interviews, developed by FAANG engineers. Practice with interview questions from top companies. Get interview-ready in just a few hours.

Beginner

230 Lessons

35h

Certificate of Completion

The ultimate guide to data structures for coding interviews, developed by FAANG engineers. Practice with interview questions from top companies. Get interview-ready in just a few hours.

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Mock Interview

Explanations

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Mock Interview

This course includes

153 Playgrounds

65 Challenges

22 Quizzes

Learn in a different language:

C++

Java

JavaScript

Python

Course Overview

Course Content

Recommendations

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

22 Lessons

Sharpen your skills in measuring and evaluating time and space complexities of algorithms.

Comparing Algorithms

Example: Measuring Time Complexity of a Single Loop Algorithm

Example: Time Complexity of an Algorithm With Nested Loops

Introduction to Asymptotic Analysis and Big O

Other Common Asymptotic Notations and Why Big O Trumps Them

Useful Formulae

Common Complexity Scenarios

Challenge: Big (O) of Nested Loop with Addition

Solution: Big O of a Nested Loop with Addition

Challenge: Big (O) of Nested Loop with Subtraction

Solution: Big O of a Nested Loop with Subtraction

Challenge: Big O of Nested Loop with Multiplication

Solution: Big O of Nested Loop with Multiplication

Challenge: Nested Loop with Multiplication (Basic)

Solution: Nested Loop with Multiplication (Basic)

Challenge: Nested Loop with Multiplication (Intermediate)

Solution: Nested Loop with Multiplication (Intermediate)

Challenge: Nested Loop with Multiplication (Advanced)

Solution: Nested Loop with Multiplication (Advanced)

Challenge: Nested Loop with Multiplication (Pro)

Solution: Nested Loop with Multiplication (Pro)

Complexity Interview Questions

Arrays

26 Lessons

Get started with arrays, lists essentials, and solving various array manipulation challenges.

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

31 Lessons

Examine linked list operations, including insertion, deletion, traversal, and efficiency comparisons.

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

25 Lessons

Grasp the fundamentals of stacks and queues, their implementations, and common challenges.

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

25 Lessons

Dig into the concepts, representation, and operations of various graph types and traversal algorithms.

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

Investigate tree types, structures, operations, and problems for efficient coding with trees.

What is a Tree?

Types of Trees

What Makes a Tree Balanced?

What is a Binary Tree?

More on Complete Binary Trees

Skewed Binary Tree

What is a Binary Search Tree (BST)?

Insertion in Binary Search Trees

Insertion in BST (Complete Implementation)

Search in Binary Search Trees (Implementation)

Deletion in Binary Search Trees

Deletion in Binary Search Trees (Implementation)

Pre-Order Traversal in Binary Search Trees

In-Order Traversal in Binary Search Trees

Post-Order Traversal in Binary Search Tree

What is an AVL Tree?

AVL Insertion

AVL Deletion

What is a Red-Black Tree?

Red-Black Tree Insertion

Red-Black Tree Deletion

What is a 2-3 Tree?

2-3 Insertion

2-3 Deletion of Element at Leaf Node

2-3 Deletion of Element at Internal Node

2-3-4 Trees

Overview of Trees

Challenge: Find Minimum Value in Binary Search Tree

Solution: Find Minimum Value in Binary Search Tree

Challenge: Find kth Maximum Value in Binary Search Tree

Solution: Find kth Maximum Value in Binary Search Tree

Challenge: Find Ancestors of a Given Node in a BST

Solution: Find Ancestors of a Given Node in a BST

Challenge: Find the Height of Binary Search Tree

Solution: Find the Height of Binary Search Tree

Challenge: Find Nodes at k Distance from the Root

Solution: Find Nodes at k Distance from the Root

Tree Interview Questions

Trie (Advanced Trees)

14 Lessons

Master the steps to construct and utilize Tries for efficient string storage and retrieval.

What is a Trie?

The Structure of a Trie

Insertion in a Trie

Search in a Trie

Deletion in a Trie

Challenge: Total Number of Words in a Trie

Solution: Total Number of Words in a Trie

Challenge: Find All Words Stored in Trie

Solution: Find All Words Stored in Trie

Challenge: Array Sort Using Trie

Solution: Array Sort Using Trie

Challenge: Word Formation From a Dictionary Using Trie

Solution: Word Formation From a Dictionary Using Trie

Trie Interview Questions

Heaps

14 Lessons

Step through the concepts and applications of heaps, their operations, and transformations.

What is a Heap

Why Use Heaps?

Heap Representation in Arrays

Max Heap: Introduction

Max Heap (Implementation)

Min Heap: An Introduction

Min Heap (Implementation)

Challenge: Convert Max Heap to Min Heap

Solution: Convert Max Heap to Min Heap

Challenge: Find k Smallest Elements in an Array

Solution: Find k Smallest Elements in an Array

Challenge: Find K Largest Elements in an Array

Solution: Find K Largest Elements in an Array

Heap Interview Questions

Hash Tables

33 Lessons

Grasp the essentials and practical implementations of hash tables, tackling collisions, and solving challenges using hashing in Java.

What is a Hash Table?

Hash Functions

Collisions in Hash Tables

Building a Hash Table from Scratch

Add/Remove & Search in a Hash Table (Implementation)

Complete Implementation of Hash Tables

Trie vs Hash Table

HashMap vs HashSet

Challenge: An Array as a Subset of Another Array

Solution: An Array as a Subset of Another Array

Challenge: Check if Arrays are Disjoint

Solution: Check if Arrays are Disjoint

Challenge: Find Symmetric Pairs in an Array

Solution: Find Symmetric Pairs in an Array

Challenge: Trace the Complete Path of a Journey

Solution: Trace the Complete Path of a Journey

Challenge: Find Two Pairs in an Array Such That a+b = c+d

Solution: Find Two Pairs in an Array Such That a+b = c+d

Challenge: A Subarray with a Sum of 0

Solution: A Subarray with a Sum of 0

Challenge: Word Formation Using a Hash Table

Solution: Word Formation Using a Hash Table

Challenge: Find Two Numbers That Add up to k—Hashing

Solution: Find Two Numbers That Add up to k—Hashing

Challenge: First Non-Repeating Integer in an Array—Hashing

Solution: First Non-Repeating Integer in an Array—Hashing

Challenge: Linked List Cycle—Hashing

Solution: Linked List Cycle—Hashing

Challenge: Remove Duplicates from Linked List - Hashing

Solution: Remove Duplicates from Linked List - Hashing

Challenge: Union and Intersection of Linked Lists — Hashing

Solution: Union and Intersection of Linked Lists — Hashing

Hashing Interview Questions

10.

Summary of Data Structures

2 Lessons

Go hands-on with linear and non-linear data structures for coding efficiencies.

Overview of Linear & Non-Linear Data Structures

Conclusion

Course Author

Coderust

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Free Resources

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.