While you are enthralled by the universe of possibilities that the expanding IT industry presents, keeping up with the profession and its different specialist skills might be difficult. Data science is one particular field that has generated a lot of excitement in the community.

If you work in the field, are a self-taught coding expert, or are simply interested in technology, you are probably familiar with computer science and the exciting programming careers associated with it—but where does data science fit in? Is one a better option for aspiring technologists than the other?

In this post, we'll compare data science with computer science to help you make sense of it all.

Basics

• To begin, consider the key contrasts between these two computer jobs. Computer science is the most ancient of the two disciplines, extending back hundreds of years. Ada Lovelace, the first "computer programmer," lived in the early 1800s, more than a century before the first modern computer was constructed. Data science, on the other hand, is a relatively young field in technology that has grown as corporations and organisations strive to make use of the huge amounts of data they collect.

• The study of the theory and practise of how computers work is known as computer science. A degree in Computer Science teaches you programming, software, operating systems, algorithms, and everything else required to run a computer.

• Computer Science students learn programming languages such as Python, JavaScript, and Java, as well as the essential principles that enable these languages to function. Operating systems, networking, security, algorithms, and computer architecture are all taught in school. Overall, computer science is entirely concerned with computers.

• Data science is an interdisciplinary field that combines computer science and statistics. Statistical analysis is not new, but the size of data sets and processing power required for analysis are.

• Data science is a specialised field that teaches students how to analyse and discover patterns in massive amounts of data.

• In data science, data is acquired (or mined) and examined for any valuable insights, trends or patterns. Data scientists process, enhance, and show their findings using computer languages such as R, SAS, Python, and Java, as well as technologies such as Hadoop, Tableau, and Apache Spark. Degrees in Data Science concentrate on mathematical principles and understanding, such as calculus and statistics. Other topics covered include machine learning, deep learning, data visualisation, and databases.

Job titles

If you're attempting to decide which topic to study, it's a good idea to be aware of the job titles that you could potentially qualify for in your career. After all, you don't see many people with the job title computer scientist heading into work, so let's shed some light on what's actually available. We used real-time data analysis to identify the top job titles for people with a Bachelor's degree in Computer Science.1 The most popular career titles for those with a Computer Science degree are: software development engineer, software developer, Java® developer, systems engineer, and network engineer.

Data scientists, data architects, data engineers, business analysts, and data analysts are all examples of people who work in the subject of data science.

Education needed 

Before entering either of these industries, you should examine the quantity of education required. Postsecondary education is required for both data science and computer science careers, but let's take a closer look at what businesses are looking for in candidates.

To be a competitive candidate in the employment market, you will most likely require a Bachelor's degree in computer science. Software developers, one of the most frequent computer science-related careers, normally require at least a Bachelor's degree, according to the Bureau of Labor Statistics.

Positions in data science, on the other hand, frequently necessitate extra education beyond a Bachelor's degree. Employers were overwhelmingly seeking applicants with at least a Bachelor's degree, according to our survey of data scientist job listings—and 31 percent of job postings were seeking people with a Master's degree.

Knowing what schooling is needed for your ideal job can help you figure out where to start. If you want to be a data scientist, you may need to put in more education hours than a software developer or programmer with a Computer Science degree. Because there is some subject material overlap, an undergraduate degree in Computer Science may be an intriguing option for aspiring data science specialists.

Key Differences Between Computer Science and Data Science

• Computer Science is the study of computations that covers subjects such as Data Structures, Algorithms, Computer Architecture, Programming Languages, and so on, whereas Data Science is the study of mathematics that includes ideas such as Statistics, Algebra, Calculus, Advanced Statistics, and Data Engineering are just a few examples.

• Computer Science teaches us about the creation and operation of processors, as well as memory management in programming domains. Data Science provides us with an understanding of how data may be utilised to analyse how data will be stored, processed, and altered to eliminate redundancy and make it relevant for future use.

• Computer Science teaches us about the operation of computer technology and its applications. Data Science explains how to extract information and knowledge from many types of data.

• Computations, probabilistic theories, reasoning, discrete structures, and database design are all subfields of computer science. Data Science encompasses simulation, modelling, analytics, machine learning, and computer mathematics, among other things.

• The core branch is computer science, while data science is a subset of computer science.

• Computer Science is entirely concerned with the effective construction and use of computers, whereas Data Science is concerned with the safe processing of data.

• Computer Science is all about computation, whereas Data Science is all about data.

• Computer science is advancing with new concepts, and more efficient and advanced gadgets are on the way. Data is becoming increasingly hard to handle and keep on a daily basis.

• Computer Science is concerned with algorithms, with a greater emphasis on software engineering and development. Data Science is the combining three fields’ data engineering, maths, and statistics.

• Computer science is concerned with scientific approaches to problem solving. Data Science is concerned with organising and processing data.

• Computer Science has several research fields to study and excel in, whereas Data Science research areas have lately evolved and expanded, providing us with more alternatives.