Data Structures from Coursera

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.

A few examples of questions that we are going to cover in this class are the following:

1. What is a good strategy of resizing a dynamic array?

2. How priority queues are implemented in C++, Java, and Python?

3. How to implement a hash table so that the amortized running time of all operations is O(1) on average?

4. What are good strategies to keep a binary tree balanced?

You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!

What's inside

Syllabus

Basic Data Structures

In this module, you will learn about the basic data structures used throughout the rest of this course. We start this module by looking in detail at the fundamental building blocks: arrays and linked lists. From there, we build up two important data structures: stacks and queues. Next, we look at trees: examples of how they’re used in Computer Science, how they’re implemented, and the various ways they can be traversed. Once you’ve completed this module, you will be able to implement any of these data structures, as well as have a solid understanding of the costs of the operations, as well as the tradeoffs involved in using each data structure.

Dynamic Arrays and Amortized Analysis

In this module, we discuss Dynamic Arrays: a way of using arrays when it is unknown ahead-of-time how many elements will be needed. Here, we also discuss amortized analysis: a method of determining the amortized cost of an operation over a sequence of operations. Amortized analysis is very often used to analyse performance of algorithms when the straightforward analysis produces unsatisfactory results, but amortized analysis helps to show that the algorithm is actually efficient. It is used both for Dynamic Arrays analysis and will also be used in the end of this course to analyze Splay trees.

Priority Queues and Disjoint Sets

We start this module by considering priority queues which are used to efficiently schedule jobs, either in the context of a computer operating system or in real life, to sort huge files, which is the most important building block for any Big Data processing algorithm, and to efficiently compute shortest paths in graphs, which is a topic we will cover in our next course. For this reason, priority queues have built-in implementations in many programming languages, including C++, Java, and Python. We will see that these implementations are based on a beautiful idea of storing a complete binary tree in an array that allows to implement all priority queue methods in just few lines of code. We will then switch to disjoint sets data structure that is used, for example, in dynamic graph connectivity and image processing. We will see again how simple and natural ideas lead to an implementation that is both easy to code and very efficient. By completing this module, you will be able to implement both these data structures efficiently from scratch.

Hash Tables

In this module you will learn about very powerful and widely used technique called hashing. Its applications include implementation of programming languages, file systems, pattern search, distributed key-value storage and many more. You will learn how to implement data structures to store and modify sets of objects and mappings from one type of objects to another one. You will see that naive implementations either consume huge amount of memory or are slow, and then you will learn to implement hash tables that use linear memory and work in O(1) on average! In the end, you will learn how hash functions are used in modern disrtibuted systems and how they are used to optimize storage of services like Dropbox, Google Drive and Yandex Disk!

Binary Search Trees

In this module we study binary search trees, which are a data structure for doing searches on dynamically changing ordered sets. You will learn about many of the difficulties in accomplishing this task and the ways in which we can overcome them. In order to do this you will need to learn the basic structure of binary search trees, how to insert and delete without destroying this structure, and how to ensure that the tree remains balanced.

Binary Search Trees 2

In this module we continue studying binary search trees. We study a few non-trivial applications. We then study the new kind of balanced search trees - Splay Trees. They adapt to the queries dynamically and are optimal in many ways.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches skills, knowledge, and tools that are core skills for developers

Examines topics that are highly relevant to computer science and programming

Taught by Alexander S. Kulikov, Daniel M Kane, Neil Rhodes, and Michael Levin, who are recognized for their work in data structures

Instructs students to focus on well-designed data structures alongside efficient algorithms

Builds a strong foundation for beginners and strengthens existing foundations for intermediate learners

Provides foundational knowledge that will help learners in various computational problems

Reviews summary

Data mastery

learners say this course is largely positive and provides them with a deep understanding of data structures. Topics covered include basics such as arrays and linked lists to more advanced ones such as priority queues and balanced binary search trees. The programming assignments are mentioned to be challenging but helpful in reinforcing the concepts learned. While some learners found the lectures to be fast-paced, they acknowledged that the course provides a good refresher for those with prior exposure to data structures. The quality of the assignments, the level of challenges, and the level of detail provided in the lectures and readings are also praised by learners. However, a few learners have reported experiencing issues with the homework assignments, including poorly written problem descriptions, hidden edge cases, and a grading system that is perceived as unfair.

The topics are presented in a logical progression, starting from basics to advanced concepts.

"Topics covered include basics such as arrays and linked lists to more advanced ones such as priority queues and balanced binary search trees."

Learners appreciate the level of detail provided in the lectures and readings, which they find comprehensive and well-explained.

"While some learners found the lectures to be fast-paced, they acknowledged that the course provides a good refresher for those with prior exposure to data structures."

"The quality of the assignments, the level of challenges, and the level of detail provided in the lectures and readings are also praised by learners."

The practice questions are challenging and facilitate understanding.

"The programming assignments are mentioned to be challenging but helpful in reinforcing the concepts learned."

Some learners found the lectures to be fast-paced.

"While some learners found the lectures to be fast-paced, they acknowledged that the course provides a good refresher for those with prior exposure to data structures."

Some learners experienced issues with the homework assignments, including poorly written problem descriptions, hidden edge cases, and a grading system that is perceived as unfair.

"However, a few learners have reported experiencing issues with the homework assignments, including poorly written problem descriptions, hidden edge cases, and a grading system that is perceived as unfair."

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 Data Structures with these activities:

Review Basic Data Structures

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Reviewing basic data structures like arrays, linked lists, stacks, and queues will prepare you for learning more advanced data structures in the course.

Browse courses on Arrays

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Go over your notes from a previous data structures course or textbook.
Work through some practice problems to test your understanding.

Join a Study Group

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Joining a study group will provide you with opportunities to discuss the course material with other students, ask questions, and work through problems together.

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Find a study group that meets your schedule and learning style.
Attend study group meetings regularly.
Participate actively in discussions.
Help other students with their understanding of the material.

Learn About Hashing Techniques

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Hashing is a fundamental technique used in many different applications. Following a tutorial on hashing will help you understand how to implement and use hash tables effectively.

Browse courses on Hashing

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Find a tutorial on hashing that is appropriate for your skill level.
Work through the tutorial, taking notes and completing any practice exercises.
Implement a hash table in your preferred programming language.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Implement a Data Structure in Your Preferred Programming Language

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Implementing a data structure in your preferred programming language will help you gain a deeper understanding of how the data structure works and how to use it effectively.

Browse courses on Data Structures

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Choose a data structure that you are interested in implementing.
Research the data structure and learn about its properties and uses.
Implement the data structure in your chosen programming language.
Test your implementation to make sure that it is working correctly.
Write documentation for your implementation.

Solve Data Structures Coding Challenges

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Solving data structures coding challenges will help you develop your problem-solving skills and improve your understanding of how data structures are used in practice.

Browse courses on Data Structures

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Find a website or platform that offers data structures coding challenges.
Choose a challenge that is appropriate for your skill level.
Solve the challenge using a data structure that is appropriate for the problem.
Review your solution and make sure that it is correct and efficient.
Move on to more difficult challenges as you improve your skills.

Read 'Data Structures and Algorithms in Java' by Michael T. Goodrich and Roberto Tamassia

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This book provides a comprehensive overview of data structures and algorithms, with a focus on Java implementations. Reading this book will help you deepen your understanding of the concepts covered in the course.

View Data Structures and Algorithms in Java on Amazon

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Read the book cover-to-cover.
Take notes and highlight important passages.
Work through the practice exercises at the end of each chapter.

Contribute to Open Source Data Structures Projects

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Contributing to open source data structures projects will allow you to learn from others, improve your coding skills, and give back to the community.

Browse courses on Open Source

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Find an open source data structures project that you are interested in contributing to.
Read the project documentation to learn about the project and its goals.
Identify an area where you can contribute.
Make your contribution to the project.
Submit a pull request to the project's repository.

Career center

Learners who complete Data Structures will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists know how to design the right data structures for any project. This course offers a great foundation for understanding how to do that. It covers a wide range of data structures used in data science, such as arrays, linked lists, queues, stacks, trees, and graphs. You'll also learn how to implement these data structures in your own code. By taking this course, you'll be well-prepared to handle the data science challenges you'll face on the job.

See salaries and explore the career path for Data Scientist

Systems Analyst

Systems Analysts design, develop, and maintain computer systems. They need to have a solid understanding of data structures in order to be able to design and implement efficient systems. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Systems Analyst

Software Architect

Software Architects design and develop software systems. They need to have a solid understanding of data structures in order to be able to design and implement efficient systems. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Software Architect

Machine Learning Engineer

Machine Learning Engineers design, develop, and test machine learning models. They need to have a solid understanding of data structures in order to build models that are efficient and accurate. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Machine Learning Engineer

Product Manager

Product Managers are responsible for planning, developing, and launching new products. They need to have a solid understanding of data structures in order to be able to manage the development process efficiently. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. They need to have a solid understanding of data structures in order to be able to organize and analyze large financial datasets efficiently. A course in financial data structures can give you the knowledge and skills you need to launch a successful career in quantitative finance.

See salaries and explore the career path for Quantitative Analyst

Project Manager

Project Managers are responsible for planning, executing, and closing projects. They need to have a solid understanding of data structures in order to be able to manage projects efficiently. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Project Manager

Business Analyst

A Business Analyst is responsible for analyzing business requirements and developing solutions that meet the needs of the business. They need to have a solid understanding of data structures in order to be able to organize and analyze large amounts of data. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Business Analyst

Data Analyst

Data Analysts collect, clean, and analyze data in order to help businesses make better decisions. They need to have a solid understanding of data structures in order to be able to organize and analyze large datasets efficiently. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Data Analyst

Database Administrator

Database Administrators design, implement, and maintain databases. They need to have a solid understanding of data structures in order to create databases that are efficient and scalable. This course can help you build the foundation you need to succeed in this role. It offers a thorough overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. Along the way, you'll learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Database Administrator

User Experience Designer

User Experience Designers design and evaluate user interfaces for websites, mobile apps, and other products. They need to have a solid understanding of data structures in order to be able to design interfaces that are efficient and user-friendly. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for User Experience Designer

Chief Technology Officer

Chief Technology Officers are responsible for overseeing the technology strategy and operations of an organization. They need to have a solid understanding of data structures in order to be able to make informed decisions about technology investments. A course in data structures can give you the knowledge and skills you need to launch a successful career in technology leadership.

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Software Engineer

A software engineer designs, develops, and tests software applications. This course may be useful for those who want to pursue a career in software engineering, as it offers a foundation in data structures. Software engineers need to have a deep understanding of data structures in order to design and implement efficient software applications.

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Technical Writer

Technical Writers create and maintain technical documentation, such as user manuals, training materials, and white papers. This course can help you build the foundation you need to succeed in this role. It offers a comprehensive overview of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You'll also learn how to implement these data structures in your own code, which will give you a valuable edge in the job market.

See salaries and explore the career path for Technical Writer

Information Security Analyst

A career in information security analysis may be more attainable with the knowledge gained in this course. The course emphasizes understanding the costs and trade-offs of using data structures. This could help an information security analyst evaluate the effectiveness and efficiency of a company's data security operations.

See salaries and explore the career path for Information Security Analyst