We may earn an affiliate commission when you visit our partners.
Course image
Marcos Costa

Here you will learn the most common algorithms and data structures and also prepare for some interview questions.

This is not an ordinary course. We will write line by line of code together and explain what is is doing. Each algorithm and data structures will be introduced to you in a easy and friendly way to understand.

It will definitely help you to get to the next level in your career. It will help you on your daily coding as well.

On this course Algorithms and Data Structures you will learn and codeEuclid, Linear Search, Insert Sort, Binary Search, Quick Sort

Read more

Here you will learn the most common algorithms and data structures and also prepare for some interview questions.

This is not an ordinary course. We will write line by line of code together and explain what is is doing. Each algorithm and data structures will be introduced to you in a easy and friendly way to understand.

It will definitely help you to get to the next level in your career. It will help you on your daily coding as well.

On this course Algorithms and Data Structures you will learn and codeEuclid, Linear Search, Insert Sort, Binary Search, Quick Sort

also Binary Tree, Linked List, Doubly Linked List, Prefix Tree or Trie Tree, Stack

and finally some coding interview questionsPrint Odd Numbers, Longest Substring Without Repeating Character (Amazon Question), Sudoku (Amazon Question)

Algorithms and Data Structures are very important topics since your choice of algorithm and datastructure will affect memory and CPU time differently.

Be ready to code and be eager to learn more.

It is priceless to have the confidence to show off your skills without fear. You will be able to prove in a whiteboard interview that you are not just good but you are awesome.

Enjoy.

Enroll now

What's inside

Learning objectives

  • Be able to read code logic differently
  • Think out of the box when solving daily problems efficiently
  • Learn the most popular algorithms and data structures
  • Understand the importance of unit testing your application
  • Get a basic understanding of maven
  • Learn how recursion works
  • Practice with some interview coding questions
  • Code a sudoku solver

Syllabus

Prepare environment and basics to execute successfully the content of this course

We will get Eclipse downloaded and installed so we can start coding our exercises.

Read more

At the end of this lecture you will have a maven project created with JUNIT dependency ready to work.

You will also have a basic understanding of what maven is and how it works.

At the end of this lecture you will understand what is JUNIT and how to write a JUNIT test.

It will be easier to show how recursion works implementing an algorithm. We will implement Euclid's algorithm. I incentive you to write the code a few times then it will get stuck on your mind and easier to write and explain.

At the end of this lecture you will be able to write Euclid's algorithm and be able to explain if someone aske you this question.

On this video you will learn Linear Search algorithm.

This lecture will teach you how to code a Linear Search. You will understand how it works and we will code it from scratch.

On this video we will create a unit test for the Linear Search algorithm. We will test the code that we just wrote on the previous lecture.

I will also exhaust a little bit about JUNIT debugging and explaining in detail how you run multiple unit test at once and check which tests worked and which tests failed.

After this class you will understand how Insert Sort algorithm works.

After this lecture you will be able to understand and code an Insert Sort algorithm.

After this lecture you will test and play with the results of the InsertSort class that we created on the lecture 9. We will use a new Assertion to test the arrays. We will also use a toString from the java.util.Arrays class to help us illustrate what our code is doing.

After this lecture you will understand what is Binary Search Algorithm and how it works.

On this lecture you will learn how to code a Binary Search Algorithm. This will be coded using a non recursive way and after unit testing we will code using recursion.

On this lecture we will unit test our Binary Search Algorithm coded on the previous lecture. We will also add some code to demonstrate what the code is doing and how many iterations are happening for the search to be completed.

On this lecture you will learn how to code the Binary Search Algorithm using recursion. We will also explore the differences between the two classes (non using recursion and using it)

On this lecture we will test the Binary Search Algorithm written using recursion. More important we will quickly debug and show the recursive calls happening.

After this lecture you will understand what is Quick Sort Algorithm and how it works.

On this lecture you will learn how to code a Quick Sort Algorithm. It will be coded using recursion. Each functionality will be explained and we will go through some more detail over the next lecture while unit testing.

On this lecture we will test the Quick Sort Algorithm written using recursion. We will quickly debug the code to understand a little better.

After this lecture you will have a clear understanding of what is a BinaryTree and how it works.

On this lecture you will learn how to code a BinaryTree. We will also implement pre and post order traversal of the tree to print the elements in sort ordered or reverse ordered. We will use recursion.

At the end you will understand what it is and how to code it.

On this lecture we will test the BinaryTree coded using recursion. We will quickly debug the code to understand a little better.

We will also use the library from Apache common lang to use ArrayUtils

After this lecture you will understand what is a Linked List and how it works.

On this lecture you will learn how to implement a LinkedList.

On this lecture we will test the LinkedList created on the previous lecture. We will also debug to have a better understanding of the code.

After this lecture you will understand what is a DoublyLinkedList and what is the difference between DoublyLinkedList and LinkedList and you will also be able to understand how it works.

On this lecture you will code and understand line by line what happens on this implementation of the DoublyLinkedList.

We will develop the remove method and as an nice extra we will override the toString method to get a nice String when we print our DoublyLinkedList

On this lecture we will unit test our DoublyLinkedList methods add and remove. We will also see the result expected by the toString that we implemented.

After this lecture you will understand what is a Prefix or Trie Tree and you will also be able to understand how it works.

On this lecture you will learn how to code a Prefix or Trie Tree and we will implement the insert method which will break a String into the nodes of the tree. The search method will be implemented on the next lecture so you can have some time do drink some water.

On this lecture you will learn how to implement the search method of a Prefix or Trie Tree

On this lecture we will test the Prefix or Trie Tree implemented on the last two lectures. We will also debug the insert method so you have a better understanding of what it is doing and how it is actually working. I broke the test in two parts to make is easier to understand.

On this lecture we will test the Prefix or Trie implemented on the lectures 30th and 31st and we will also debug the search method so you have a good understanding of what it is doing and how it is actually working.

On this lecture you will understand what is a Stack and how it works.

On this lecture you will learn how to implement a Stack and this implementation will be using Object as the object being stored. The next lecture we will refactor this code to implement generics.

On this lecture we will test the Stack implemented on the previous lecture and we will also debug so you have a better understanding of what it is doing and how it is actually working. A refactor using Generics will be done on the next lecture.

On this lecture we will refactor the stack developed on the previous lecture and refactor to implement generics

On this lecture we will test the Stack with Generics implemented on the previous lecture and we will also debug so you have a better understanding of what it is doing and how it is actually working.

On this lecture we will code the interview question to print the odd numbers. We will also implement a second way to the problem.

On this lecture we will unit test the print odd numbers interview question. We will also debug and do a small refactor to make it fancier and cleaner.

On this lecture you will understand what is this question all about and how we are going to proceed to implement it on the next lecture.

On this lecture we will implement this interview question that returns the number of characters and comment through the code.

On this lecture we will refactor the code implemented on the previous lecture to also make available the sequence of characters and not just the count. We will also comment as we code for you to have a better understanding.

On this lecture we will unit test our interview exercise find the longest substring without repeating characters. We will also debug the code to get it in a bit more detail

Sudoku was broken in two coding parts to make it easier for you. On this lecture we will implement the first part of the Sudoku interview question and comment through the code.

On this lecture we will implement the second part of the Sudoku interview question and comment through the code. We will implement all the methods necessary to have the solve method working properly.

On this lecture we will create unit test for all the methods that we developed to have the sudoku working. We will test solve and printMe on the next lecture.

On this lecture we will test the solve method, debug through the code and check the output using the printMe method implemented.

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Covers common algorithms and data structures, which are essential for technical interviews and daily coding tasks, making it highly relevant for career advancement
Includes hands-on coding exercises and unit testing, providing practical experience and reinforcing theoretical concepts, which is useful for building confidence
Uses JUnit for unit testing, which is a standard tool in Java development, and familiarizes learners with industry best practices
Introduces Maven for project management, which is a widely used build automation tool in the Java ecosystem, and helps learners manage dependencies
Focuses on coding interview questions, such as Longest Substring Without Repeating Character and Sudoku solver, which are commonly asked by tech companies
Requires learners to download and install Eclipse, which may pose a barrier for those unfamiliar with IDEs or who prefer other development environments

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Practical java algorithms and data structures

According to learners, this course provides a solid foundation in fundamental algorithms and data structures using Java. Many appreciate the practical approach, with the instructor coding along line-by-line, making concepts easy to follow, especially for those new to the topics or looking for a quick refresher. The course is particularly praised for its focus on job interview preparation, directly addressing relevant questions. However, some students note that the depth of coverage might be too basic for intermediate or advanced learners and suggest that additional practice or supplemental material is needed for true mastery.
Covers basic ADTs and algorithms in Java.
"Covers the essential basic algorithms and data structures well."
"A good introduction to common data structures like Linked Lists and Trees."
"The course covers fundamental sorting and searching algorithms."
"Provides a solid overview of key computer science concepts."
Instructor codes along, encouraging practice.
"Coding line by line with the instructor was extremely beneficial."
"I really liked the hands-on coding examples throughout the course."
"Following the coding step-by-step helped solidify my understanding."
"Actively writing the code made learning much more effective."
Concepts are explained simply, good for beginners.
"The explanations were very clear and easy to grasp."
"Great course for anyone starting out with Algorithms and Data Structures."
"Complex topics are broken down into simple, digestible parts."
"I found the teaching style very accessible and beginner-friendly."
Course is highly relevant for coding interviews.
"This course truly helped me prepare for my technical interviews."
"The interview questions section was invaluable for my job search."
"A great resource specifically designed for coding interview preparation."
"I felt much more confident tackling interview problems after this."
Supplemental problems needed for mastery.
"You will definitely need to practice problems outside the course."
"This course is a starting point; don't rely only on its examples."
"To master DSA, external practice resources are necessary."
"I needed to seek out more coding challenges to truly learn."
Might be too basic for advanced learners.
"This course might be too basic if you already have some DSA background."
"Could benefit from more advanced topics or optimization techniques."
"The depth is introductory; intermediate students may need more."
"I felt some topics were covered quite superficially."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Algorithms and Data Structures Easy Way Java - job interview with these activities:
Review Java Fundamentals
Solidify your understanding of Java fundamentals to better grasp the implementation of algorithms and data structures in this course.
Show steps
  • Review data types, operators, and control flow in Java.
  • Practice writing simple Java programs.
  • Study object-oriented programming concepts in Java.
Review 'Cracking the Coding Interview'
Study common interview questions and solutions to prepare for job interviews.
Show steps
  • Read the chapters on data structures and algorithms.
  • Practice solving the coding problems in the book.
  • Review the solutions and explanations provided.
LeetCode Easy Problems
Reinforce your understanding of algorithms and data structures by solving easy-level problems on LeetCode.
Show steps
  • Select a set of easy-level algorithm problems on LeetCode.
  • Attempt to solve each problem independently.
  • Review the solutions and discuss alternative approaches.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Help Others on Forums
Reinforce your understanding by helping other students on online forums.
Show steps
  • Find online forums related to algorithms and data structures.
  • Answer questions and provide explanations to help other students.
  • Explain your reasoning and provide code examples.
Create a Blog Post on Algorithm Analysis
Deepen your understanding of algorithm analysis by writing a blog post explaining time and space complexity.
Show steps
  • Research different algorithm analysis techniques.
  • Write a clear and concise explanation of time and space complexity.
  • Provide examples of how to analyze the complexity of different algorithms.
  • Publish the blog post on a platform like Medium or your personal website.
Implement a Simple Search Engine
Apply your knowledge of data structures and algorithms to build a practical project that simulates a search engine.
Show steps
  • Design the data structures for storing web pages and their content.
  • Implement indexing algorithms to create a search index.
  • Develop a search algorithm to retrieve relevant pages based on keywords.
  • Test and refine the search engine's performance.
Review 'Introduction to Algorithms'
Expand your knowledge of algorithms with a comprehensive textbook.
Show steps
  • Read the chapters related to the algorithms covered in the course.
  • Work through the examples and exercises in the book.
  • Compare the book's explanations with the course materials.

Career center

Learners who complete Algorithms and Data Structures Easy Way Java - job interview will develop knowledge and skills that may be useful to these careers:
Algorithm Developer
An algorithm developer focuses on designing and implementing efficient algorithms for various applications. This course helps build a strong foundation in the core concepts of algorithms and data structures. The course's coverage of search and sort algorithms, such as linear search, binary search, and quicksort, directly applies to the work of an algorithm developer. Moreover, the hands-on coding exercises and interview preparation provide practical experience in algorithm implementation. For those who wish to master algorithm design and implementation, this course helps in the journey.
Software Engineer
A software engineer designs, develops, tests, and maintains software applications. This course helps build a foundation in algorithms and data structures, which are essential for efficient software development. Understanding different algorithms, such as linear search, insert sort, binary search, and quicksort, allows a software engineer to select the best approach for each task. The course also introduces various data structures, including binary trees, linked lists, and stacks. This course may be useful for anyone seeking to improve problem-solving skills and prepare for technical interviews.
Computer Programmer
A computer programmer writes code to implement software applications and systems. This course helps build foundational knowledge in algorithms and data structures, which are essential for efficient and effective programming. Understanding the trade-offs between different algorithms and data structures allows the computer programmer to make informed decisions about the best approach for each task. The course's hands-on coding exercises and emphasis on unit testing provide practical experience in writing robust code.
Software Development Engineer in Test
A Software Development Engineer in Test designs and implements tests to ensure software quality. This course helps build a solid foundation in algorithms and data structures, which is beneficial for writing effective test cases. Understanding the behavior of different algorithms, such as search and sort algorithms, allows a software development engineer in test to design comprehensive tests. The unit testing focus in the course is particularly relevant, as it teaches how to write and execute tests to verify code correctness. For developing a strong testing foundation, this course can be considered.
Mobile App Developer
A mobile app developer specializes in creating applications for mobile devices. This course helps build a solid foundation in algorithms and data structures, enabling the creation of efficient and responsive mobile applications. Understanding various algorithms, such as search and sort algorithms, helps optimize app performance. The course's focus on coding and problem-solving helps develop the skills needed to build robust mobile apps. The knowledge of Java in this course may be applied to mobile app development targeted at Android devices.
Data Scientist
A data scientist analyzes large datasets to extract meaningful insights and develop predictive models. This course may be useful for a data scientist, as it introduces fundamental algorithms and data structures. For example, understanding binary trees and search algorithms can aid in efficient data retrieval and analysis. The course's focus on coding and problem-solving helps a data scientist develop the skills needed to manipulate and analyze complex datasets. Furthermore, exposure to interview questions in the course can prepare a data scientist to ace technical assessments.
Application Developer
An application developer designs and develops software applications for computers and mobile devices. This course may be useful to an application developer, as it covers essential algorithms and data structures. Understanding sorting and search algorithms, as well as data structures like linked lists and binary trees, improves application performance and efficiency. The course's emphasis on hands-on coding and unit testing helps to develop robust and reliable applications. This course can provide the right kind of tools to solve problems in application development.
Machine Learning Engineer
A machine learning engineer develops and deploys machine learning models. This course may be useful to a machine learning engineer, as it provides a foundation in algorithms and data structures. Understanding search algorithms and data structures like trees is useful for many machine learning tasks. The coding exercises in the course can help machine learning engineers implement and optimize their models. This course may be valuable for those who want to enhance their machine learning skills.
Backend Developer
A backend developer is responsible for the server-side logic and database management of web applications. This course may be useful to a backend developer, as it covers data structures and algorithms that are crucial for optimizing application performance. Understanding how to implement and use data structures like linked lists, stacks, and binary trees can improve the efficiency of database operations and API development. The course's focus on coding in Java can help backend developers write efficient and scalable server-side code.
Research Scientist
A research scientist conducts research to advance scientific knowledge. For those seeking a research-oriented career, this course may be useful in enhancing algorithm design and problem-solving skills, which are crucial in many research areas. The hands-on coding exercises and coverage of fundamental algorithms, such as search and sort algorithms, help build a foundation for developing novel algorithms and approaches. A graduate degree, such as a PhD, is typically required for this role.
Full-Stack Developer
A full stack developer works on both the front-end and back-end of web applications. This course may be useful to a full stack developer, as it covers algorithms and data structures that are important for optimizing both client-side and server-side performance. Understanding different algorithms, such as search and sort algorithms, allows the full stack developer to select the best approach for each task. This course can be helpful in the development journey.
Data Engineer
A data engineer builds and maintains the infrastructure for data storage and processing. While this role focuses on infrastructure, this course may be useful by providing a solid understanding of algorithms and data structures. Understanding data structures like linked lists, stacks, and trees helps in designing efficient data storage and retrieval systems. The course's emphasis on Java coding helps data engineers implement efficient data processing pipelines. This course is potentially helpful for anyone working with data infrastructure.
Systems Architect
A systems architect designs and oversees the implementation of complex computer systems. This course may be useful to a systems architect, as it reinforces fundamental knowledge of algorithms and data structures. Understanding the performance characteristics of different algorithms and data structures helps the systems architect make informed decisions about system design and optimization. The course may not be directly related to day to day tasks, but it provides valuable insights into system performance.
Database Administrator
A database administrator manages and maintains databases, ensuring data integrity and availability. This course may be useful to a database administrator, as it covers data structures that are fundamental to database design. Understanding data structures like trees and linked lists helps in optimizing database performance and storage. While the course is not specific to database administration, it does provide a valuable foundation in data structures.
Technical Lead
A technical lead manages a team of software engineers and provides technical guidance on projects. While this role often requires extensive experience, this course helps to reinforce fundamental knowledge of algorithms and data structures. While a technical lead might not write code every day, a strong understanding of algorithms is essential for making architectural decisions and guiding team members. The course provides a refresher on key concepts and an exposure to coding interview questions. Such content may be useful in guiding and mentoring junior developers effectively.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Algorithms and Data Structures Easy Way Java - job interview.
Is specifically designed to help software engineers prepare for coding interviews. It covers a wide range of data structures and algorithms, along with common interview questions and detailed solutions. Given the course's focus on interview preparation, this book is an invaluable resource for practicing and mastering the skills needed to succeed in technical interviews.
Comprehensive textbook on algorithms, covering a wide range of topics including data structures, sorting, searching, graph algorithms, and dynamic programming. It provides rigorous analysis and clear explanations, making it suitable for both beginners and advanced learners. It is often used as a primary textbook in university-level algorithms courses and provides a strong theoretical foundation for the practical implementation covered in the course.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Similar courses are unavailable at this time. Please try again later.
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser