What is the difference between data science and computer science?

So what is given?

It can be difficult to discern the real differences between two closely related fields, especially for those not involved in the technology field. And even for people in the tech industry, there can be a gray area as to what fits into each bucket.

The good news is that both data science and computer science are growing fields in terms of educational content and job opportunities. There is a growing number of degrees, certifications, and bootcamps that teach in-demand hard skills like programming, machine learning, and data analysis that are perfect for each field. Furthermore, salaries for engineers remain high. According to Dice, the average salary for a technician in 2023 was $111,193.

But the question remains: What is the real difference between data and computer science? This article provides some insights.

What is data science?

As the name suggests, data science focuses on collecting, organizing, and extracting data within the context of real-world problems, often in business. Fortune has a comprehensive guide that delves more specifically into the intricacies of data science.

Studying data science often leads to careers such as data scientist, data analyst, or data engineering. According to the U.S. Bureau of Labor Statistics, data-related occupations are growing faster than the national average for all occupations in the United States, with data scientists in particular growing at a rate of 35%. Additionally, their salaries are high, with an average annual salary of approximately $103,500.

Data science skills center around programming languages ​​such as SQL, R, and Python, as well as knowledge of statistics, mathematics, and AI.

Jignesh Patel, a professor at Carnegie Mellon University and co-founder of DataChat, says data science is a subfield of computer science and is an offshoot of machine learning and big data statistics.

“Just like a doctor might specialize in pediatrics or surgery, a computer scientist might specialize in data science,” Patel says.

What is computer science?

Computer science is a broader term that focuses on the study of computers, including software, hardware, networks, and AI.

“A career in computer science encompasses a very wide range of roles, including software development, software engineering and architecture, computer security, and database development and management,” said Mamdough Refaat, Chief Data Scientist at Altair. .

From a degree perspective, computer science programs offer a variety of fields and specializations, including data science, cybersecurity, machine learning, and AI. As a result, those who study computer science are not necessarily confined to the title computer scientist. Software developers, systems analysts, and computer engineers are just a few examples.

Overall, computer science-related roles are in high demand, and most have average salaries near or within six figures, based on data from the U.S. Bureau of Labor Statistics.

What is the difference between data and computer science?

The main difference between data and computer science is the level of focus. Computer science is a more comprehensive field of study that also includes data science itself.

For computer science, differentiating skills may include improving your knowledge of computer networking, cybersecurity, and algorithms. Computer scientists may know a variety of programming languages, including JavaScript, C++, and HTML. This subject can also be combined well with other non-technical fields such as physics and economics.

Data science, on the other hand, is a much more niche subfield that is more closely related to mathematics and statistics. Key skills include machine learning, AI, and deep learning know-how. Additionally, the programming languages ​​involved are more specific and include SQL, R, and Python.

It’s not very common to find certifications or bootcamp programs in “computer science.” Instead, they may focus on topics such as IT, data analytics, AI, and cybersecurity.

“The two fields intersect in the areas of artificial intelligence, data management, and programming,” Refaat tells Fortune. “However, you could say that computer science focuses on creating programming environments and software in general, whereas data science focuses on exploring and using data.”

As both fields continue to grow, Refaat adds, professionals should expect lifelong learning, especially when it comes to solving business problems.

“Employers in every industry are looking for data and computer scientists who have a deep understanding of a particular industry and its unique problems and applications,” he says. “The basic skills in both fields are transferable across industries, but having business acumen is a big advantage.”