Computer Science vs. Data Science: Decoding Your Ideal Career Path

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While you are fascinated with the world of possibilities that the booming tech industry promises, it can be a challenge to keep up with the field and its various niche specialties. One specialty area that’s been the center of a growing buzz in the community is data science.

If you currently work in the field, are a self-taught coding connoisseur or are simply in-touch with tech, you are probably at least somewhat familiar with computer science and the exciting programming careers tied to the field—but where does data science fit in? Is one a better option for tech hopefuls to pursue than the other?computer science pdf computer engineering vs computer science computer science jobs computer science course computer science binus

In this article, we’ll break down data science versus computer science to help you make better sense of it all.

Data Science vs. Computer Science: The Basics

To begin, let’s explore the fundamental differences between these two computer careers. Computer science is the older of the two subjects, dating back hundreds of years. In fact, the first “computer programmer,” Ada Lovelace, lived in the early 1800s—over a hundred years before the first modern computer was created. On the other hand, data science is a relatively new field in technology that has grown as businesses and organizations seek to put the massive amounts of data they collect to good use.computer science pdf computer engineering vs computer science computer science jobs computer science course computer science binus

Computer Science is the study of the theory and practice of how computers work. “When you earn a degree in Computer Science, you learn programming, software, operating systems, algorithms and everything needed to run a computer,” says Nirupama Mallavarupu, founder of MobileArq. “You learn to solve problems using technology.”

Those who study Computer Science learn programming languages such as Python®, JavaScript® and Java®as well as the fundamental elements that make these languages work. In school, topics such as operating systems, networking, security, algorithms and computer architecture are taught as well. Overall, computer science focuses solely on computers.

Data science isn’t as clear cut; it’s an interdisciplinary field involving computer science and statistics. Statistical analysis is nothing new, but the scale of the data sets and computing power needed for analysis certainly are.

“Data science is an advanced discipline that teaches students how to analyze and find patterns in large amounts of data,” Mallavarupu says.

In data science, data is gathered (or mined) and analyzed for any valuable insights, trends or patterns. Those in a data science field use programming languages such as R, SAS, Python® and Java®, and software such as Hadoop, Tableau and Apache Spark to process, refine and display their findings. Data Science degrees focus on mathematical concepts and understanding, such as calculus and statistics. Other subjects such as machine learning, deep learning, data visualization and databases are also covered.

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