What’s The Difference Between Data Science and Computer Science?


Last Updated on August 27, 2021

As we all know, Data Science is termed as the most wanted job of the 21st century. This statement alone has such an impact, that most folks today are now interested in Simplilearn data science certification. But as we all know, some prerequisites help a data scientist stand out from others. One of those prerequisites is Computer Science skills or knowledge.

Most new learners of any data science certification course assume Data Science and Computer Science to be the same fields. In this post, we’ll go through some fundamental differences between Data Science and Computer Science. So, let’s get started.


The study of computation and information is called Computer Science (CS). It’s a broad field of study which in general deals with the study of computer design and architecture, computation, algorithms, computational problems, design of computer systems hardware, software, networking, internet, and applications.

The core idea is to study computers and its related concepts. This study is made to apply this knowledge in other fields like science and technology, business, agriculture, etc. It has a vast number of areas to research.

Data Science (DS) is a specialized field that deals with various types of data to extract some information using multiple mathematical concepts, like statistical and descriptive methods, with the help of numerous present-day technologies. The critical intent here is to generate insights (data) from the vast amount of data available today. These insights are then used by the business to make better-informed decisions.

Scope of Field:

Computer Science covers all the technological fields. The study of computer science leads to technological advancements. Technically, it’s a superset of Data Science.

Data Science covers all studies of the data-related field. Innovations in mathematical approaches and technology lead to advancement in Data Science. Technically it’s a subset of computer science.


The study of Computer Science has been in existence for many years now. It even is offered as an academic subject for research for decades.

The Data Science field though being centuries-old (in terms of studying the mathematical concepts and algorithms the Data Science uses today), has recently come to light with advancements in technology. It is now a developing branch of Science and Technology. It’s currently being offered as an academic subject for study.


Computer Science focuses more on topics like Algorithms, Data Structure, Programming Languages, Computer Architecture, Network Architecture, Operating Systems, etc.

Data Science focuses more on subjects like Basic and Advanced Statistics, Calculus, Data Engineering, Big Data, Machine Learning, Artificial Intelligence, etc.

End Goal / Usage / Benefits:

Technological growth and advancement are some of the benefits of the study of Computer Science. The development of efficient algorithms, applications, fast and robust systems are some of its other end goals. The study of computer science provides us with super-fast and computationally powerful systems, tools, and techniques. In the end, this is used by any end-user (Eg., Software professionals) to perform other tasks or solve real-world problems.

Computer Science fields mostly use programming languages, algorithms, or super-fast computers to solve real-world problems.

The end goal of Data Science is to get something useful out of the data. In this process, we inherently try to wrangle, inspect, and manage data. The benefit of performing data science is that we can better understand the data, i.e., it gives answers to questions like a better understanding of user behavior, purchase patterns, which product should be given more importance, etc.

The Data Science field uses large volumes of data for analysis and insights for the business.


restaurant data chart

There are, in general, no prerequisites to study Computer Science, except for the interest in the field of study of computers. An individual with good logic building and basic computer knowledge can benefit from quick learning in computer science.

Today anyone with no relevant background or domain knowledge can start learning Data Science. To completely master it, one must know some essential calculus, statistics, and some high-level programming languages like R or Python. Along with it, interest in dealing with vast amounts of data will make you successful in the Data Science field.

Industry / Applicants:

Computer Science generally applies to all technical product or service-oriented industries and companies which make use of Information Technology (IT) or CS technologies in their business.

It is the base of the IT industries. Hence, the support for anyone who wants to be an IT/software professional. Though people from other fields are actively joining CS-based roles and profiles, people with relevant IT / CS background are preferred for the respective profiles.

The CS job may include one or a few of the following activities: Programming, Application Maintenance, Admin / Support work, System design / Architect, Desktop Support activities, etc.

Data Science generally applies to companies directly or indirectly dealing with large volumes of data. These companies have data that has one of their sources of income.

Technology giants like Google, Microsoft, or Amazon rely heavily on studying the data generated from using their services. One who aspires to be a Data Analyst or Data Scientist can explore in this field.

The DS job generally includes one or a few of the following activities: Data Cleaning, Data Wrangling / Manipulation, Model building, Big data management, and other activities.

Hurray. You made it to the last. Taking the effort to do research and clear out confusion is the first step in learning, and you have just completed the same—Pat yourself on the back.


Data Analytics

In this post, we have covered some of the fundamental differences between computer science and data science fields in terms of study, history, prerequisites, usage, industry, and profession. After reading this post, we hope that most of your confusion surrounding Computer Science and Data Science must have been cleared. Hopefully, this will help all the new learners who are planning to do data science certification.

Tags: advanced analytics vs data science ai vs big data career analytical data analysis analytics background analytics data science & artificial intelligence analytics data science data analysis and predictive analytics for business analytics machine learning difference analytics vs analysis analytics vs data science android developer vs data scientist applied statistics vs data science are data science and data analytics same are data science and machine learning the same are data science masters worth it arkansas center for data sciences reviews associate degree in data science bachelor of computer science data science bachelors degree in data science become a data scientist no technical background best major for data science best way to learn data science and machine learning big data analytics and data science difference big data analytics data scientist big data analytics falls under big data analytics vs data mining big data analytics vs data science big data and data science difference big data and machine learning big data and machine learning course big data and machine learning difference big data developer vs big data analyst big data everyone talks about it big data for commerce background big data learning approaches big data machine learning big data scope in canada big data software engineer salary big data vs android big data vs big data analytics big data vs data analytics big data vs data science vs data analytics big data vs data science vs machine learning big data vs data science which is better big data vs deep learning big data vs machine learning big data vs machine learning which is better breakdown of data bsc computer science with data analytics business analytics computer science business analytics vs data science business data scientist can a data scientist become a software engineer can you become a data scientist with a bachelor’s degree careers for data science majors cloud computing vs big data salary computer analytics computer and data engineering computer courses salary computer cyber security computer data scientist computer engineering and data science computer engineering cybersecurity and artificial intelligence computer engineering vs cyber security computer information systems vs cyber security computer networking vs computer science computer programming cyber security computer programming vs cyber security computer science analytics computer science and cyber security computer science comes under which stream computer science cyber security computer science cyber security salary computer science data analytics computer science data science computer science degree for cyber security computer science for cyber security computer science for data scientists computer science network and security computer science or cyber security computer science or data science degree computer science security computer science security degree computer science vs cyber security computer science vs cyber security degree computer science vs machine learning computer science with a concentration in cyber security computer science with specialization in data science computer security study consulting vs data science cs cyber security cse data science cyber security or software engineer cyber security scientist cyber security vs data analyst cyber security vs game development cyber security vs software development cyber security vs software development salary cyber security vs software engineering cyber security vs web development cyber security with a computer science degree cybersecurity computer security cybersecurity subfields cybersecurity vs networking data analitic data analysis and data analytics difference data analysis in software engineering data analysis university data analysis vs data science data analysis vs statistical analysis data analyst associate degree data analyst big data data analyst college major data analyst course for commerce students data analyst data scientist data analyst degree data analyst education programs data analyst machine learning data analyst non technical data analyst or data scientist data analyst scientist data analyst vs programmer data analytics vs coding data and computer science data science and computer science data science bachelor degree jobs data science cs data science in computer networking data science is a branch of computer science data science or computer science data science or computer science masters data science streams data science vs computer science which is better data science vs data analytics vs machine learning data science vs information science data science vs information systems data science vs programming data science vs software development data scientist computer data scientist vs programmer information systems vs data science ms in data science vs ms in computer science what is data analysis in computer science what is data analytics in computer science

Click here for Source

Yorum Yaz

Your email address will not be published.