Data science and computer science are the two buzzwords among companies and learners. Everyone wishes to pursue a degree in computer or data science to get a lucrative job. They aren’t wrong, however! Data science and computer science can help students get high-paying offers without difficulties. Do you know? An average data science job can give you an annual salary of $97,254. In contrast, a Bachelor’s degree in CS can fetch you an average pay of $91,000 per annum.
However, many people often get confused between data science and computer science. These concepts have significant differences. It’s better to know how these courses vary before choosing any one of them. These topics have various scopes and futures for students enrolled in related programs. This post will cover everything about comparing data science and computer science.
So, let’s make an informed decision for your career with a detailed discussion. You can make the best choice between a computer science course and a data science program by reading this article.
Let’s get started!
Meaning of Data Science
Data science combines several fields to extract value from data, including statistics, analysis, scientific techniques, and artificial intelligence or AI. Data scientists are people with a wide range of skills that analyze data from the web, consumers, smartphones, sensors, and other sources to provide actionable insights.
Data science is known as data investigation. It is done by identifying sources, cleansing, aggregating, and changing data to do advanced data analysis. The data can then be analyzed by analytic software and data scientists to find patterns and help business leaders make better decisions.
Computer Science Defined
Computer science is the research of computers and computing systems. Unlike electrical and computer engineers, computer scientists specialize in designing, theory, developing, and implementing software and relevant procedures.
Computer science includes essential topics such as artificial intelligence, security, computer systems and networks, database systems, numerical analysis, human-computer interaction, vision and graphics, programming languages, bioinformatics, software engineering, and computing theory.
Programming is an integral aspect of computer science, although it is only one facet of the discipline. Computer scientists develop and study algorithms to solve issues and investigate the performance of computer hardware and software. Computer scientists handle numerous abstract and concrete problems, like determining what problems you can solve with computers and the algorithms’ sophistication. Computer scientists design applications that efficiently perform on handheld devices and manufacture simple-to-use products while complying with security measures.
Data Science vs. Computer Science – The Battle Begins!
You have already understood the differences between computer science and data science definitions. But, hey! The comparisons aren’t over yet. We can state more points to differentiate between computer science and data science. And it will help if you learn these aspects before you can make the perfect career decision for yourself.
So, let the battle between computer science and data science begin right below. Stay tuned till the end!
- Variety of subjects taught under computer and data science
Computer science is the field of computations merging various concepts like Data Structures, Algorithms, Computer Architecture, Programming Languages, etc. In contrast, data science comprises mathematics concepts, such as Statistics, Algebra, Calculus, Advanced Statistics, Data Engineering, etc.
- The essence of data science and computer science
Computer science teaches us about processor architecture, operation, and memory management in programming. Data science gives us a perspective on using data to investigate how data is stored, processed, and altered to decrease redundancy and make it useful for subsequent use.
- Purpose of data science and computer science
Computer science provides us with in-depth knowledge of how computers are used and what applications computers have in the modern landscape. Data science explains how to extract knowledge and information from many data types.
- The difference in sub-areas
Computations, reasoning, probabilistic theories, discrete structures, and database design are all sub-areas of computer science. Simulation, analytics, modeling, machine learning, and computational mathematics are all examples of data science.
- Interdependence
Data Science is a domain of computer science, while computer science is the primary umbrella.
- Their futures
With each passing year, the breadth of Data Science expands. People throughout the world entered the digitization era in the 20s.
The tremendous growth of data offers a peek at Data Science’s future potential in India.
Candidates can now pursue new opportunities in fields such as Machine Learning (ML), Blockchain development, Data Science, Artificial Intelligence (AI), Augmented and Virtual Reality (AR/VR), Robotics, Cloud and Big Data, Mobile app development, Data Mining, and the Internet of Things (IoT). Computer science, on the whole, has a broader reach than data science.
These were the core differences between computer science and data science. However, that’s not all! You can walk through more comparisons to better understand computer science vs. data science.
Here are the other differences between the two branches:
- Data science is all about carefully handling data, while computer science is about efficiently developing and using computers.
- Data science is data computing, whereas computer science is all about computing.
- Technological concepts in computer science are advancing, and more efficient and advanced gadgets are on the way. Data is increasing in volume and complexity, making it increasingly difficult to manage and preserve.
- Algorithms are the subject of computer science, which focuses on software engineering and development. Data science synthesizes three disciplines: data engineering, mathematics, and statistics.
- Computer science is concerned with the use of scientific methods to solve problems. Finding a way to organize and process data is what data science is all about.
- There are several research topics in computer science to pursue and achieve in jobs. On the other hand, data science study topics have recently become more advanced and expanded, giving us more alternatives.
Conclusion
Data science and computer science are bright career pathways. You can choose any of them depending on your core interests. It’s better to pursue data science if you are obsessed with data. However, if you want to learn all concepts under the giant umbrella of computer science, choose a CS program.
The choice is yours ultimately!
