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Data Structures

Learn data structures with online courses and programs

Data structures are essential to computer science. They enable data storage, management, and processing, making it easy for users to retrieve data for a variety of purposes. Learn about data structures with online courses delivered through edX.

What are data structures?

A data structure is a specialized format used to store, process, and retrieve data. By providing a unique framework for each set of data, these programmatic building blocks streamline information access and management.

Data structures typically fall into two overarching categories: linear and nonlinear. Linear data structures involve ordered sequences of elements and offer simple implementation for non-complex programs. There are four major linear data structure types:

Arrays, in which elements of the same type are stored contiguously
Stacks, in which the last element is processed first
Queues, in which the first element is processed first
Linked lists, in which elements are linked through nodes, or contiguously arranged data units

Nonlinear data structures contain non-sequential arrangements of elements. In these structures, each element is linked to one or more elements. Nonlinear data structure types include:

Graphs, which consist of nodes (also known as vertices) that are linked through edges

Trees, in which any two vertices can be linked by only one edge

In addition to linear and nonlinear classifications, data structures can also be static or dynamic. Static data structures are arranged in a fixed format that cannot be changed. Alternatively, dynamic data structures adapt to the information present at any given time, growing or shrinking to fit the data.^{Footnote 1}

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Data structures course curriculum

Data structures are the building blocks of programming, driving efficiency and organization from the ground up. By taking a data structures course, aspiring programmers can gain the skills they need to thrive in today’s increasingly tech-driven landscape.

A fundamentals course can help new learners get up to speed with the basics of data structures. Before studying advanced concepts, learners may explore common data structures through hands-on exercises. Specialized topics can provide in-depth knowledge of algorithms, software engineering, and programming frameworks.

Data structures are also a foundational component of computer science. Learners interested in pursuing a computer science education may find it beneficial to explore related data structure classes in Java data structures or object-oriented programming. edX provides a variety of options to begin learning about using data structures in different fields

Explore jobs that use data structures

Many roles require a thorough understanding of data structures. These may include:

Data engineer: These engineers develop and optimize complex databases and systems, design algorithms, and oversee data retrieval and storage.^{Footnote 2} By mastering data structures concepts, they can maximize efficiency and recognize crucial patterns. These are both must-have skills for those who work with large amounts of data.^{Footnote 3}
Software engineer: Software engineers drive and oversee the entire development process, from conception to launch. This requires advanced programming knowledge, a skill set that includes a strong background in data structures.^{Footnote 4}
Developer: These programming experts are often tasked with testing, designing, and overseeing software development. In order to do so, they need to understand Python, Java, C++, and other popular programming languages.^{Footnote 5} By familiarizing themselves with data structures, developers can devise more dynamic and efficient solutions.

Expertise in data structures can be tremendously valuable for many roles. However, it isn’t necessarily a requirement for every programming or data role. Some employers may prefer candidates with specialized knowledge, while others may require a bachelor’s or master’s degree.

How to become a data engineer online

Specialized training can give aspiring data engineers the edge they need to stand out. Beyond gaining a solid command of data structures, learners can benefit from studying:

Structured Query Language (SQL), a crucial programming language used for relational database management.^{Footnote 6}
Data analysis, including popular analytics tools.
Cloud platforms, such as Amazon Web Services (AWS) and Microsoft Azure.

In general, requirements vary by role and company. Certain jobs require a bachelor’s or master’s degree. Others may call for specific boot camp certifications. Specific options for your education may include a bachelor’s in computer or data science or even a master’s in data science. For shorter courses of study, a data analytics boot camp may be the experience you are looking for.

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Frequently asked questions

Why learn data structures and algorithms?

Strong knowledge of data structures and algorithms enables tech professionals to develop more efficient and dynamic solutions to a wide range of data-related challenges.

Are data structures easy to learn?

Mastering data structures can be challenging, especially for less experienced learners. You can streamline the process by sharpening your problem-solving skills, better acquainting yourself with technical language, and seeking out additional guidance. Building a solid foundation can take anywhere from several weeks to several months, depending on initial experience and course intensity.

What are stacks and queues?

Stacks and queues are linear abstract data types (ADTs). Stacks follow the “last in, first out” (LIFO) approach, in which the last element of a sequence is processed first. It can be thought of like a stack of books, which can only be altered from the top. Queues, by contrast, are characterized by “first in, first out” (FIFO), in which the first element in is processed first.^{Footnote 7} A grocery store checkout line is an example of a queue, because the person who is first in line will check out first.

Do data structures vary by programming language?

Syntax refers to the rules that dictate proper arrangements of symbols and characters, which can vary.^{Footnote 8} For example, C++, Java, and Python are case-sensitive languages, while Basic and SQL are case-insensitive.^{Footnote 9} Overarching data structure concepts, on the other hand, do not vary.

Which language is best for data structures?

While no language is necessarily better than others, C++ is a highly efficient language for data structures. It offers a number of advantages when it comes to memory management, time complexity, and data flow. That said, the language is simply a medium. Programmers can implement data structures in any language they’re proficient in.

Are data structures necessary for web development?

Within web development, knowledge of data structures isn’t essential. However, the industry has evolved greatly over the last decade, with many web professionals prioritizing a full-stack skill set. In today’s increasingly technical web development space, familiarity with data structures can help learners gain a deeper understanding of the systems they’re working on.