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What is the Difference Between Computer Science and Data Science?

What is the Difference Between Computer Science and Data Science?

Programmer in front of desktop computer writing code

Don’t be fooled by the names—computer science and data science are not the same. It’s crucial to recognize that computer science and data science represent distinct fields with unique characteristics. The intricacies of their differences shape your career trajectory and influence the training and education you should pursue in each realm. At its core, computer science, often encompassing data science, stands as a broader discipline with diverse applications. On the other hand, while interconnected with computer science, data science possesses nuanced elements that extend into realms like business analytics and data visualization. This exploration aims to dissect the specifics of computer and data science, aiding you in determining the most fitting path for your career. To assist in this decision, questions like “Which is better, a master’s in computer science or a master’s in data science?” will be addressed.

In this blog, we’ll take a closer look at the specifics, like career paths, training, and education, of computer and data science to help you determine which path is the best for you.

What is Computer Science?

Computer science is the study of computers, including computational theory, hardware, software, algorithms, and the ways that humans interact with technology.1 Simply put, it’s the study of the various parts that make up a computer and the numerous activities for which you can use them. Just as the computer itself has evolved tremendously since its first model in 1938, so has the field of computer science.2

First, it’s important to note that what constitutes a computer has changed drastically over the last decade. While you might think of a traditional desktop computer or laptop, the definition of a computer is more broadly “an electronic device that manipulates information, or data…it has the ability to store, retrieve, and process data.”3 As you’ve likely already experienced, you can use a computer to type documents, store photos, send emails, play games, browse the internet, create spreadsheets, watch videos, and more.

In a field as vast and diverse as computer science, you’ll be able to explore many different focus areas, such as software engineering, computer security, databases, and information security. As mentioned above, computer science can also overlap with elements of data science, including artificial intelligence and data engineering. The wide range of concentrations can make computer science more difficult to define, so let’s look closer at the requirements and career paths for a professional computer science position.

Education & Background

Professionals who work in computer science usually are more automation and object-orientation-focused—many of them may fall under the “left brain” stereotypes vs. the right brain—and have a background in computer or software engineering.4

Some of the tools and languages a computer scientist can expect to use are:

  • IDEs
  • Testing software
  • Python and other programming languages
  • Microsoft Azure
  • Atom
  • GitHub

In terms of educational background and requirements, the best way to land a job in computer science is to earn a computer science bachelor’s and/or master’s degree. Although it’s not essential that you earn a master’s degree in computer science to work in the field, it gives you an advanced set of skills, a deeper knowledge of the subject matter, and an overall higher distinction than those who only complete a bachelor’s degree.

Once you determine that a master’s degree in computer science is right for you, then you can begin the process of selecting a university and specific degree program. Pay attention to the degree name and curriculum, as it likely means there’s a specialization or specific career path in mind.

Computer Science Careers

The breadth of applications for computer science means there’s an equally high number of career options. Read job descriptions carefully to make sure they align with your experience, skills, and interests before moving forward; you may often find that a computer scientist role is actually for a data scientist, or a hybrid of the two.

With a master’s degree in computer science, you can pursue these job titles:

  • Computer and information research scientist
  • Software developer or software engineer
  • Information security analyst
  • Cybersecurity expert
  • Web developer or designer
  • IT director
  • Network specialist
  • AI scientist

As for the employment outlook in computer science, the future is bright. Overall employment for computer and information research scientists is projected to grow 21% from 2021 to 2031, which is much faster than the average for all occupations.5 Data also shows that a master’s in computer science paves the way to jobs that pay, on average, $30,000 more than those who only have an undergraduate degree in computing, and almost $60,000 more for those who come from outside the field of computing.6

What is Data Science?

In today’s data-saturated world, data science has become one of the most important tools for success. Data science combines computer programming skills, domain expertise, and an understanding of mathematics and statistics to extract knowledge and insights from data. It is multi-disciplinary and uses scientific processes, methods, systems, and machine learning algorithms to make connections, predict outcomes, and uncover new hypotheses within and between datasets.The advanced systems that data scientists create and monitor can generate valuable insights, which is crucial for 21st century business. The more that stakeholders can understand about their customers, prospects, products, operations, employees, the more efficient and profitable they can become.

Data science usually attracts individuals with backgrounds in statistics and data analysis—again, more scientific and logic-based minds tend to gravitate to this discipline. However, data science professionals work with everything from text and numbers to audio, video, and images, which creates a lot of opportunities for creativity as well.

Another benefit of data science is that there are many different specializations you can pursue. This can include business intelligence, data mining and statistical analysis, data visualization, database management, data engineering, cybersecurity data analysis, data analytics, machine learning, and artificial intelligence. From there, you can work in multiple industry sectors as diverse as telecommunications, health, agriculture, retail, finance, information technology, and professional services.7

Education & Background

Similar to computer science, the best and most efficient path toward a data science career is to earn a bachelor’s and/or master’s degree. In the field of data science as a whole, a master’s degree is often expected, if not required. Thus, to qualify for the positions that you want, it’s an extremely beneficial addition to your resume, not just for the esteem it conveys, but also for the advanced knowledge and skills that it will give you (and which employers will expect you to possess). Even better, studies show that data scientists with a master’s degree earn an average of 17% more than those with just an undergraduate degree.8

The top skills that employers look for in data science are:

  • Computing theory
  • Advanced data science
  • Machine learning
  • Data visualization
  • Statistics
  • Programming languages (SQL, R, SAS, Python, etc.)
  • Deep learning

If you choose to pursue a master’s degree, consider how the program will help you hone your specialty or generally advance your career. At the end of the Online Data Science, M.S. program, you can choose to complete a thesis as part of your degree. You also will have the chance to work on funded research projects with faculty members from sponsors such as the U.S. Department of Defense, National Science Foundation, and National Institutes of Health.

Data Science Careers

With so much valuable data on the line, companies are increasingly invested in finding the right people to help them capitalize on it—and they’re paying them well, too. Employment of data scientists is projected to grow 36% from 2021 to 2031, much faster than the average for all occupations.9 With an average salary of about $137,854, a booming job market, and impressively high job satisfaction, ‘data scientist’ was ranked the third best job in America in 2022.10,11

Potential job titles in data science include:

  • Data scientist
  • Database administrator
  • Machine learning engineer
  • Data engineer
  • Analytics manager
  • Quantitative analyst

Find the Best of Both Worlds at New York Tech

Now that you know more about the similarities and differences between data science and computer science, you can take the next steps you need for your career. Whichever path you choose, you can be confident that you’re gaining skills and knowledge that will be in demand for years to come.

Building on your undergraduate studies in computer science or data science with an online master’s degree is an efficient and effective way to achieve your personal and professional goals. The classes and coursework are offered entirely online and can be completed whenever, and wherever, works best for you. Every aspect of the online master’s programs—the faculty, content, and learning outcomes—are exactly the same as our on-campus degrees, but require less time and money to complete.

With a master’s-level designation, as well as the valuable New York network and career resources that New York Tech provides, you’ll find that the Online Data Science, M.S. is an extremely valuable investment in your future. So much so, in fact, that New York Tech is ranked No. 9 in New York and in the top 10% in the U.S. for Return on Investment (ROI) among low income students.12 As one of the top 25 universities in the region, we pride ourselves on putting our students and their needs first.13

Interested? Set up some time to talk with an Admissions Advisor, or take the first step by starting an application.

New York Institute of Technology has engaged Everspring, a leading provider of education and technology services, to support select aspects of program delivery.