Algorithms for Coding Interviews in Java

This course helps you crack the coding interview by mastering the solution of real coding interview problems using various algorithms in Java.

Intermediate

151 Lessons

15h

Certificate of Completion

This course helps you crack the coding interview by mastering the solution of real coding interview problems using various algorithms in Java.

AI-POWERED

Mock Interview

Explanations

AI-POWERED

Mock Interview

Explanations

This course includes

140 Playgrounds

50 Challenges

17 Quizzes

This course includes

140 Playgrounds

50 Challenges

17 Quizzes

Course Overview

Algorithms are one of the most common themes in coding interviews, so having a firm grip on them can be the difference between being hired or not. After this comprehensive course in Java, one of the most popular coding languages, you'll have an in-depth understanding of different algorithm types and be equipped with a simple process for approaching complex analysis. As you progress through the course, you’ll be exposed to the most important algorithms that you're likely to encounter in an interview. You'l...Show More

TAKEAWAY SKILLS

Java

Programming Language

Prepare For Interview

Algorithms

Time Complexity

Course Content

Introduction

In this chapter, you will discover how to enhance your coding skills in Java through algorithmic concepts and practical challenges for technical interviews.

Intended Audience

Learning Outcomes

Algorithmic Paradigms

This chapter covers algorithms, like brute force, greedy approach, divide and conquer, and dynamic programming, with their strategies and applications.

Asymptotic Analysis

In this chapter, you will learn how to evaluate algorithms' efficiency through asymptotic analysis, focusing on time complexity and practical examples.

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

Sorting and Searching

This chapter explores sorting and searching algorithms, detailing their efficiencies and challenges to improve your problem-solving skills in coding interviews.

Selection Sort, Bubble Sort, and Insertion Sort

Merge Sort

Quicksort

Time Complexities of Sorting Algorithms (Overview)

Searching Algorithms

Challenge: Find Two Numbers that Add up to "n"

Solution: Find Two Numbers that Add up to "n"

Challenge: Search in a Rotated Array

Solution: Search in a Rotated Array

Challenge: Group Anagrams

Solution: Group Anagrams

Challenge: Find the Median of Two Sorted Arrays

Solution: Find the Median of Two Sorted Arrays

Challenge: Find Duplicates in Array

Solution: Find Duplicates in Array

Challenge: Search in Sorted Matrix

Solution: Search in Sorted Matrix

Challenge: Count Element Occurrence

Solution: Count Element Occurrence

Challenge: Search Insert Position

Solution: Search Insert Position

Challenge: Sparse Search

Solution: Sparse Search

Challenge: Dutch National Flag Problem

Solution: Dutch National Flag Problem

Quiz on Sorting & Searching

Dynamic Programming

This chapter focuses on dynamic programming techniques, emphasizing optimization for algorithmic challenges to enhance efficiency in problem-solving.

Greedy Algorithms

20 Lessons

In this chapter, you will learn how to solve problems using greedy algorithms by making optimal local choices for efficient solutions.

Divide and Conquer

23 Lessons

This chapter covers the divide and conquer approach, illustrating its applications, challenges, and efficient solutions for various problems.

Graph Algorithms

22 Lessons

In this chapter, you will explore essential graph algorithms, including various traversals such as BFS and DFS, and their practical implementations.

Appendix: Auxiliary Source Code

5 Lessons

This chapter discusses essential Java data structures like Stacks, Queues, PriorityQueues, HashMaps, and ArrayLists.

10.

Conclusion

2 Lessons

This chapter shows how to solve technical interview preparation by emphasizing algorithm analysis and suggesting further specialized courses.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

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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Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Put your skills to the test in a simulated interview setting. Receive personalized feedback based on your performance. Available in Premium & Premium Plus plans.

Adaptive Learning

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AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Frequently Asked Questions

How do I prepare for a Java coding interview?

Focus on mastering data structures (arrays, linked lists, stacks, queues, trees, graphs) and algorithms (sorting, searching, dynamic programming). Practice on platforms like Educative. Get comfortable with Java-specific features like collections, generics, and streams. Time management is crucial, so simulate timed coding interviews.

Is Java a good choice for coding interviews?

Yes, Java is a great language for coding interviews. It offers a balance of readability, ease of debugging, and rich built-in libraries for data structures and algorithms. Many top tech companies expect candidates to use languages like Java for coding interviews.

How do I improve my Java coding skills?

Regularly practice coding problems, explore open-source projects, and review Java’s core concepts like OOP, exception handling, and multithreading. Read code written by experienced developers, contribute to Java forums, and stay updated with Java’s latest features.

How do I write fast code in Java?

Write efficient algorithms by understanding time and space complexity. Use appropriate data structures from Java’s collections framework and avoid unnecessary memory allocations. Opt for primitive data types where possible and utilize Java’s profiling tools to identify and optimize bottlenecks.

Why is Java good for algorithms?

Java is widely used for algorithms due to its high-level abstraction and performance balance. Its rich libraries (like java.util) provide efficient implementations of common data structures, making it easy to focus on problem-solving. Additionally, Java’s strict typing helps catch errors early during development.