Popular Data Structures Certification and Course Options in 2025

Data structures are a foundational concept within computer science and software development. These provide the tools you need to organize and store your data—skills every programmer needs to write scalable and effective code. In fact, data structures (often paired with data algorithms) are frequently one of the first concepts introduced to beginner programmers. 

You likely won’t find any certification options devoted solely to data structures. However, you can choose from several data science credentials that include the topic within their robust frameworks. Additionally, you can also consider completing an online course, especially one that provides a completion certificate, to help demonstrate your knowledge and skills to potential employers. To find the right learning option for you, explore some popular options that can help you build confidence and competence in data structures. 

What does a data structure certification and course cover?

A typical data structure course or certification will focus on how you can store, organize, and manipulate your data efficiently. Data structures are containers that allow you to organize and format your data in a way that your computer program or system can process and retrieve it. This provides a way for your program to perform tasks like searching, updating, or deleting data.

Something to note is that data structures go hand in hand with data algorithms. While data structures define how you store data, algorithms define how you manipulate this data. Many courses teach both together, so you can learn to write efficient code and solve complex data challenges.

Data structure basics

Data structure courses typically introduce you to basic structures and when to use each. When learning about data structures, you’re likely to come across common data structures such as the following.

Arrays 

With an array, you can store elements in a fixed-size, ordered list. You might also use arrays for sorting and searching, which is considered a foundational element for other data structures. For example, if you were recording learner test scores, an array might look like:

Test_scores = [97, 85, 72, 99, 89]

Linked lists

A linked list is an arrangement of data elements in which every element points to the next. You might use this if you’re organizing a playlist, instructions, or a series of events. You can insert and delete items easily with this structure, without having to redo the series. If you were creating a lineup for a music festival, your linked list might look like:

Set 1 - Set 2 - Set 3 - Set 4

Stacks 

A stack is a structure that follows the “last-in, first-out” rule. You can think about this like stacking bricks. The top brick is the most recent element you added, and only the brick on top of the stack can be removed. If you want to remove or use recent items, this structure provides convenience. 

The “undo” button on your computer is a prime example of this. When you press “undo,” it eliminates the most recent action you took.

Queues 

Queues are the opposite of stacks—they follow the “first in, first out” rule, which means the first element you add will also be the one removed first. You might use this type of structure to create priority queues, especially when it comes to waiting lists. 

This type of structure is helpful for call centers, for example, where the representative should connect to the caller who has been on the line the longest. 

Trees and graphs

If you have interconnected data with a hierarchical structure, trees and graphs provide a way to organize data. With a tree, you could search people in a company based on who they report to or the department they are in. With a graph structure, on the other hand, you have more flexibility to define complex connections between entities, such as mapping social networks or clusters of people within organizations.

Hash tables

If you have a large amount of data that you want to be easily retrievable, a hash table uses a hash function to store unique data values. This is essentially a digital key that corresponds to a particular location in the computer’s memory. By using the hash, you can quickly search, add, and remove data from the structure.

A typical example of this is a phone book. By entering a specific number or name, you can quickly find the information of the person or organization in the directory.

3 data structures certification options

Certifications offer industry-recognized credentials that affirm you have particular skills or knowledge. Although no providers offer certifications specific only to data structures, you might consider a data science accreditation that includes data structures as part of its scope. After all, having a solid understanding of data structures and algorithms is essential for storing and exchanging data, creating big data applications, and managing resources. A few examples to consider include the following. 

1. Professional Data Engineer

Provider: Google 

Level: Beginner to intermediate

Cost: $200 [1]

Making data usable is an essential part of what data engineers do. This credential from Google has no prerequisites, although it will be helpful to have three or more years of relevant experience. It covers various practices ranging from collecting and processing data to designing systems and automating workloads. 

2. SAS Certified Data Scientist

Provider: SAS

Level: Professional 

Cost: $180 [2]

Having a strong foundation in data structures can help you apply SAS programming and data manipulation skills effectively. These are just two of the topics you’ll need to master for this certification, which also assesses your ability to use machine learning models to drive business decisions, utilize SAS to manipulate big data to derive insights, and broadly implement models using SAS tools. You’ll need to earn your SAS Certified Professional: Advanced Programming, and then obtain your SAS Certified Professional: AI and Machine Learning or SAS Advanced Analytics Professional. 

3. Principal Data Scientist 

Provider: DASCA

Level: Expert

Cost: $750 to $1,450 [3]

The Principal Data Scientist (PDS) credential from the Data Science Council of America (DASCA) certifies your expertise in data science and your standing as a leader in the field. This high-level certification for executives and innovators requires a broad knowledge base, including areas like shaping data science trends, architecting solutions, and using data to help your organization achieve its objectives. 

Big data features in several sections of the exam, and having solid knowledge and practical experience with data structures can be invaluable. DASCA offers four ways to gain entry to this certification program: by invitation, employer nomination, having its Senior Data Scientist (SDS) certification, or via open application. 

5 popular data structures courses with certificates 

If you want an option that focuses more specifically on data structures and algorithms, a course or certificate program may be a better option. These options offer a more focused credential that integrates instruction to help you build your skills and knowledge base, ultimately awarding you a certificate to acknowledge your mastery of the materials and completion of the program.

As a prospective computer programmer or data professional, having a solid understanding of how to store and access data provides a basis for designing more complex algorithms and applications. 

1. Data Structures and Algorithms by Amazon

Provider: Amazon via Coursera

Level: Beginner

Time to complete: Four weeks at 10 hours per week 

Cost: Free with Coursera Plus, which is $59 per month

If you want to learn basic data structures and algorithms in Java, including how to search, sort, and optimize your data processing, this Data Structures and Algorithms course could be helpful for you. It’s part of the Amazon Junior Software Developer Professional Certificate, and can help you strengthen your core programming skills through hands-on exercises with data structures and algorithms. You’ll work through four modules, where you can learn about structures such as arrays, linked lists, stacks, queues, ArrayLists, and maps, and how to evaluate the performance of each. 

By the end, learners often feel confident with topics such as recursion, algorithmic logic in Java, testing for sorting and searching algorithms, and building reliable data structures for different applications. 

2. C++: Data Structures and Algorithms Specialization by Codio

Provider: Codio via Coursera

Level: Intermediate

Time to complete: Three months at four hours per week

Cost: Free with Coursera Plus, which is $59 per month

If you have a basic foundation in C++ and want to expand your knowledge into more complex object-oriented programming and control structures, consider this Specialization. This three-course series focuses on essential data structures and algorithms that every programmer should know, from linear structures (e.g., linked lists and stacks) to advanced nonlinear structures such as trees and hash tables. 

One of the benefits of this Specialization is that you have the opportunity to build your portfolio with projects such as developing a Wordle solver or a guest reservation system. The applied learning project provides a project you can upload to GitHub, helping to build your online presence and stand out to potential employers. 

3. Data Structures and Algorithms Specialization by UCSD

Provider: UC San Diego via Coursera

Level: Intermediate 

Time to complete: 6-8 months at 10 hours per week

Cost: Free with Coursera Plus, which is $59 per month

If you learn by doing and want to build a deep, university-level foundation in data structures and algorithms, consider putting your skills into practice with this Specialization. This six-course series stands out for its implementation-driven approach. It was developed by a team of computer scientists at UC San Diego and a former Google engineer to go beyond theory and drill into hands-on practice. You’ll have the opportunity to complete nearly 100 hands-on coding challenges in the language of your choice to reinforce your understanding of data structures.

This Specialization offers the same depth of content as Algorithm 101 courses at top universities and provides an opportunity to build a strong portfolio of algorithmic projects. Plus, you can gain experience with advanced data sets, such as big networks (e.g., social media) and genome assembly projects.

4. Advanced Data Structures in Java

Provider: UC San Diego

Level: Intermediate to advanced

Time to complete: About 25 hours

Cost: Free with Coursera Plus, which is $59 per month

If you have prior experience with Java and prefer a mix of didactic and hands-on learning, consider taking this course to begin learning advanced concepts while applying them to a real-world data science challenge. You will have an opportunity to create a route planning application (similar to Google Maps). As each module introduces more complex topics, you’ll be able to apply what you learn and incrementally enhance your model. 

This course focuses on graph structures, which are essential for representing structured data such as geographic networks. You’ll start by learning about graph structures, followed by weighted graphs, shortest path algorithms, complexity theory, and approximation algorithms used in large-scale problem solving. 

5. Foundations of Data Structures and Algorithms Specialization

Provider: University of Colorado Boulder

Level: Advanced

Time to complete: 4-6 months at 10 hours per week

Cost: Free with Coursera Plus, which is $59 per month

If you have a strong mathematics and Python programming background, this Specialization may familiarize you with the tools you need to develop high-performing data science applications. You’ll gain exposure to a broad range of advanced data structures, like trees and hash tables, as well as advanced sorting, searching, traversal, and shortest path algorithms.

This course includes a focus on writing efficient, well-structured code using object-oriented programming techniques. As you move to more complex projects and applications, this focus can provide a strong foundation for more efficient coding practices. By completing this course, you can also earn credit toward CU Boulder’s online master’s programs in Data Science and Computer Science

Alternative ways to learn about data structures

If an online course doesn’t suit your learning style or goals, you can opt for different options to learn new concepts and apply your skills. Some avenues to explore include:

• Do you learn best by watching examples and want a low-commitment option? Try the @takeUforward or @NeetCode channels on YouTube to explore example code and concepts.

• Do you want to invest in a more traditional, formal learning pathway to build a broad computer science foundation? Consider a computer science or data science degree.

• Do you want to learn by trial and error without a time or financial investment? Complete free tutorials on sites like Google or with a book, such as An Open Guide to Data Structures and Algorithms.

Learn more about data structures on Coursera 

Earning a data structure credential provides a defined learning pathway you can use to build foundational skills in data structures, algorithms, and applications. On Coursera, you can explore how to build data structures in the coding language of your choice, with options in Java, C++, and more. For example, the Meta Database Engineer Professional Certificate offers a comprehensive option for you to learn to create databases from scratch and learn how to add, manage, and optimize your database.