Actually most "computational" type programs are "applied" versions of the more broad major. It simply didn't exist as a word before 2012 and wasn't mainstream before 2015-2016. Computer Science Salaries. The computer science approach, on the other hand, leans more to algorithmic models without prior knowledge of the data. Applied Math? Berkeley's overall acceptance rate is 17%, but its Computer Science acceptance rate is only 8.5%. If you really can't decide:

. Stats is boring. I'm prepared to work my butt for either.,There's no easy answer. The outlook in terms of career prospects is positive. CS vs. Statistics. From 2015 to 2018, the percentage has gone from 16% to 15%, where it has remained unchanged. It appears that formal university training in Data Science evolves as a hybrid between Computer Science and Statistics, with a technical focus towards Big Data technologies. See what you like better.

,The prerequisites for both classes should be really similar at least until sophomore year with the exception of maybe one or two extra classes which might fill some other graduation requirements. And at a tech company like Twitch, it’s clear that applying those learnings requires a deep understanding of computer science. For a Junior or Senior looking for a reliably easy AP, Computer Science is not the way to go. The outlook in terms of career prospects is positive. vs. Statistics? Data science is a combination of three fields, and you'll see people define the job as any of the three, interchangeably and/or in combination: data engineering, math + statistics… Computer science graduates enjoy excellent career prospects as the majority of businesses worldwide require personnel skilled in programming, systems analysis and the management of computer resources. Data science will investigate and inspect data to deduce factual, quantitative and statistical inference. Do you want to build robots and develop autonomous systems? You do not necessarily need to use a computer to do statistics, but you cannot really do data science without one. In other words, computer science deals with programming software and hardware where data science deals with analytics, programming, and statistics. Marketing + coding = growth hacking. For a Junior or Senior looking for a reliably easy AP, Computer Science is not the way to go. Statistics is another broad subject which deals with the study of data and is widely applied in numerous fields. A lot of the best data scientists I know come from fields that aren’t the fields normally associated with data science like machine learning, statistics, and computer science.” Therefore, data scientists are considered to be familiar with business models and paradigms, who ask good business questions to obtain meaningful insights from given data sets. This has been a guide to Data Science vs Statistics. Though an IT and computer science degree can both prepare you for jobs in the tech field, they often appeal to different types of people based on the slightly varied skill sets. 14. Use the interactive table below to filter the rankings by location, and click on individual universities for more information. Data Science is the combination three fields’ data engineering, maths, and statistics. Posted by u/[deleted] 11 months ago. System.out.println(new Random().nextBoolean() ? Intervenient November 14, 2010, 7:38pm #1

Hey everyone,

Let it be known that I have no real knowledge in either, so I'm starting on the same grounds for both. bullshit) machine learning/data science courses. And maybe, statistics + coding = data science. While there’s plenty of variation between individual jobs in both fields, there are some common duties found across occupations for both. Hadoop, Data Science, Statistics & others. There is no reason to think lesser of yourself or even to compare yourself to your classmates. Statistics is used for data mining, speech recognition, vision and image analysis, data compression, artificial intelligence, and network and traffic modeling. CS vs. Statistics. On the other hand, statistics provides the methodology to collect, analyze and make conclusions from data. Data science is also a part of computer science but it requires a lot more knowledge of maths and statistics. When considering a data science degree vs. statistics degree, it’s important to understand the underlying similarities. Computer science is the study of algorithmic processes, computational machines and computation itself. About 1/4 of my Statistics courses are computer science based (C programming, SAS programming, Discrete Mathematics, Numerical Calculus, and some upper level Stats classes that require programming skills). In 2018, UC Berkeley was ranked as the nation's best public university by US News. Categorical data refers to unique data, examples are blood group of a person, marital status, etc. Applied Math vs. Computer Science vs. Statistics Thread starter avant-garde; Start date Apr 8, 2009; Apr 8, 2009 #1 avant-garde. Statistics was primarily developed to help people deal with pre-computer data problems like testing the impact of fertilizer in agriculture, or figuring out the accuracy of an estimate from a small sample.

,I hope more can provide some input as to what I should look into.

,You feel intimidated by the intelligence level of tour schoolmates? Prospective Students Undergraduate Postgraduate International PhD Programme Research News. An unchanged top five universities lead this year’s ranking of the best places to study computer science & information systems, with Massachusetts Institute of Technology (MIT) continuing to perform particularly well in our employer reputation survey. Data science vs. computer science: Education needed Before jumping into either one of these fields, you will want to consider the amount of education required. ALL RIGHTS RESERVED. Computer science degree recipients not only work for technology companies, but also frequently enter the finance sector and the retail industry, experts say. Let’s consider the CS issue first. Data Science is closer to Computer Science and Statistics is closer to mathematics, they both deal with data so they meet in the middle. Given below is the key differences between Data Science and Statistics: Data science combines multi-disciplinary fields and computing to interpret data for decision making whereas statistics refers to mathematical analysis which use quantified models to represent a given set of data. When considering a data science degree vs. statistics degree, it’s important to understand the underlying similarities. Both terms have similarity, but there is a significant difference between the two. Data science vs statistics is the term in which data science is a reaction to a narrow view to analyze data and statistics have a border idea to convey the origins. If you’ve been looking into data science you probably have some questions. Also, you'll likely find that a lot of people in college talk themself up because they have inferiority complexes and are usually doing worse than you.

,IMO, a degree in Statistics (which is rarer) can separate you from those with degrees in Computer Science (which is more common).

,There is a lot of crossover between the two degrees. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy, New Year Offer - All in One Data Science Bundle (360+ Courses, 50+ projects) Learn More, 360+ Online Courses | 1500+ Hours | Verifiable Certificates | Lifetime Access, Data Scientist Training (76 Courses, 60+ Projects), Tableau Training (4 Courses, 6+ Projects), Azure Training (5 Courses, 4 Projects, 4 Quizzes), Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes), Data Visualization Training (15 Courses, 5+ Projects), Data Scientist vs Data Engineer vs Statistician, Business Analytics Vs Predictive Analytics, Artificial Intelligence vs Business Intelligence, Artificial Intelligence vs Human Intelligence, Business Intelligence vs Business Analytics, Business Intelligence vs Machine Learning, Data Visualization vs Business Intelligence, Machine Learning vs Artificial Intelligence, Predictive Analytics vs Descriptive Analytics, Predictive Modeling vs Predictive Analytics, Supervised Learning vs Reinforcement Learning, Supervised Learning vs Unsupervised Learning, Text Mining vs Natural Language Processing, Design and implementation in 4A’s – Data Architecture, Acquisition, Analysis and Archival, Applying advanced techniques in mathematics and statistics to model data for deep analysis, Adequate programming and development skills, algorithm development skills, Deciding the type of data required to address a given problem, Analysis to be done to draw conclusions from data, Assessing the effectiveness of results and to evaluate uncertainties, Design for planning and conducting research, Descriptions which implies exploring and summarizing data, Making predictions and inference using the phenomena represented by data. Archived. Applied Math? Finally, both degrees can lead to careers in similar work settings, such as government, life and social sciences, healthcare, or engineering. Data science in simple terms can be understood as having strong connections with databases including big data and computer science. The following list, from payscale.com, shows average computer science … "Computer Science" : "Statistics");

Eh, there's kind of a big difference. Most sciences require students to be able to do some sort of computational modelling.

,Looking at the different degree programs, I'll likely stick with stats, but try and talk to the C.S. Data science vs. computer science: Common job duties . Data science is more oriented to the field of big data which seeks to provide insight information from huge volumes of complex data. This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. So, if a computer scientist concentrates on programming, statistics, and analytics, he/she can become a data scientist. It is clear that statistics is a tool or method for data science, while data science is a wide domain where a statistical method is an essential component. Ultimately, these come together in attempts to solve problems. Which one will have the most job opportunities in the near future (10 years approx)? There are some things, but the majority will not be statistics related in a traditional sense. Data science—and its differentiation from statistics—has deep roots in the history of computers. A stats major is more interested in the outcome of data analysis (which is most often done with a computer) in order to make inferences and decisions - is more of an analytical person.

,You may want to look into the "computational" type majors, like Computational Math, Computational Engineering/Science. IT vs. computer science: The basics. The Statistics and Computer Science major is designed for students who would like a strong foundation in computer science, coupled with significant advanced coursework in statistics. Data scientists use methods from many disciplines, including statistics. Computer science and software engineering may share some overlapping commonalities, however, the principles behind each field of study can offer several differences. That's why theory is important right? The methods provided by statistics include. Because you an apply it and get the hang of the newer and newer stuff being released?

. In addition, nowadays businesses consider the internet as their primary information channel due to the growing role of social web and for its business potential. I really need to pick something and stay with it :/,Computer science is more fun. In fact, data science belongs to computer science yet remains different from computer science. All this data is of much interest to a data scientist because by using these data many problems can be solved for organizations, and also societies. Data science is one of the rapidly emerging trends in computing and is a vast multi-disciplinary area. A GPA of 3.25 is required for Distinction, 3.5 for High Distinction, and 3.75 for Highest Distinction. The Computer Science deals with algorithms with more focus on software engineering and development. And the irony is, today, more women than men earn college degrees, even as the number of women studying computer science is falling. 189 0. Machine learning is generally taught as part of the computer science curriculum, and statistics is taught either by a dedicated department or as part of the math department. One common way of dividing the field is into the areas of descriptive and inf… Both data science and computer science occupations require postsecondary education, but let’s take a … Data science is also a part of computer science but it requires a lot more knowledge of maths and statistics. Useful information easily gets buried in big data which is made up of blogs, audio/video files, images, text messages, social networks, and so on. I know that in the long run it won't matter that my CS degree was in Science or Arts, but I fear that a computational route might mean that I'd miss out on some of the more theoretical classes which could help me stay competitive in the job market.

,That's why theory is important right? There are a number of ways the roles of statisticians and computer scientists merge; consider the development of models and data mining. Statistics could mean a lot of things in relation to computation, but probably not really computer science. Because you an apply it and get the hang of the newer and newer stuff being released? Both degrees focus on developing skills pertaining to data analysis, and both have courses designed to develop strong computer skills. Computer Science vs. Computer Engineering; Cyber Security vs Computer Science; Data Analyst vs Data Scientist; Data Analytics vs. Business Analytics; Data Science vs. Machine Learning ; Resources; About 2U; Data Science vs. Machine Learning. It appears that formal university training in Data Science evolves as a hybrid between Computer Science and Statistics, … Statistics is highly significant in data related studies because it helps in. As a discipline, computer science spans a range of topics from theoretical studies of algorithms, computation and information to the practical issues of implementing computational systems in hardware and software.. Its fields can be divided into theoretical and practical disciplines. It gives different methods to gather data, analyze them and interpret results and is widely used by scientists, researchers, and mathematicians in solving problems. They use specific programming languages, like C++ and JAVA, to implement specific algorithms. All this data is just noise unless it is analyzed and useful information is extracted from them. But of course, that's a personal choice....

,There's no harm in taking a probability or stats class your first and also taking a programming class. A statistical background is essential for understanding algorithms and statistical properties that form the backbone of computer science. For more information on the program structure and content, view the Science Undergraduate Handbook. Studying Computer Science (CS) at UC Berkeley. A data scientist must have skill sets to analyze and simplify problems using complex data sets to figure out information, whereas a statistician will use the techniques of numeric and quantitative analysis. Statistics was primarily developed to help people deal with pre-computer data problems like testing the impact of fertilizer in agriculture, or figuring out the accuracy of an estimate from a small sample. Use cases in data science are similar to data analytics – they begin with a clear problem statement and decision to finally end with well-defined metrics. Also to note, all statisticians cannot become data scientists and vice-versa. Close. If you want to be a data scientist, get a BSc in computer science and do a minor in math and if you can fit it in do a 2nd minor in statistics. A major in computer science will provide you with the knowledge and skills needed to innovate in information technology, and create fundamentally new IT solutions to future challenges. Computer science vs statistics major If you are deciding between majoring in statistics or computer science, you might want to know more about what each major has to offer. Computer science-related degrees also see a relatively low percentage of female graduates. Computer Science vs. Software Engineering: 10 Key Differences November 27, 2020 . To clarify Developing the perspectives on a few analysts, this paper supports a major tent perspective on data study. The QS World University Rankings by Subject are based upon academic reputation, employer reputation and research impact (click here to read the full methodology). Another important aspect to consider when deciding between Data Science and Computer Science for your education is the type of work you’d like to be doing. You do not necessarily need to use a computer to do statistics, but you cannot really do data science without one. If I want to read some books, I'll do so. There is no "data science" scientific field, there are no "data science" professors. Typically, statistical approach to models tends to involve stochastic (random) models with prior knowledge of the data. At my school we were only really exposed to the liberal arts, and not many opportunities were available for those wanting to pursue the sciences or math. That alone is basically the prerequisites to take serious (ie not big picture/toy stuff "for everyone!" Expanding beyond statistics. IMO, a degree in Statistics (which is rarer) can separate you from those with degrees in Computer Science (which is more common). The foundation requirement (5 courses) includes Computer Science 11 and 15, Mathematics 70, one course in ethics and social context (Philosophy 24 or Engineering Management 54), and a statistics course chosen from MATH 162, EE 24 or 104. “And it kinda makes sense,” Brad continues. In contrast, data science is a multidisciplinary field which uses scientific methods, processes, and systems to extract knowledge from data in a range of forms. Computer science deals with scientific ways of finding a solution for a problem. Statistics provides the methodology for making conclusions from data. In fact, the comparison doesn’t make much sense. According to Larry Wasserman: In his blog, he states how the same concepts have different names in the two fields: Robert Tibshirani, a statistician and machine learning expert at Stanford, calls machine learning “glorified statistics." Statisticians use these statistics for several different purposes. Try your hand at both and maybe you could even double major.

,I'm going to add more and see what you guys think.

,I originally applied to college as an English major due to my double 5s on the AP tests. [quote] Data science is a specialized skill and can be understood as: Therefore, it is apparent that data science is an interdisciplinary area and needs varied skill sets to gain mastery in this domain. In other words, computer science deals with programming software and hardware where data science deals with analytics, programming, and statistics. Key Differences Between Data Science and Statistics. Recently a number of new terms have arisen, such as data science, Big Data, and analytics, and the popularity of the term machine learning has grown rapidly. Most do not consider AP Computer Science 'math' enough for it to play that role, hence the surge in AP Statistics. Computer Science (Online MCIT UPenn) vs Statistics (Online MS @ Texas A&M) Question. We are aware that, big data is mostly available in unstructured formats and contains non-numeric data. for the degree of Bachelor of Science in Liberal Arts & Sciences Major in Statistics & Computer Science. I'd hope that these can help to sufficient stepping stones for college and a more mathy major.

,I think one of the worst problems I have is my inferiority complex. Most do not consider AP Computer Science 'math' enough for it to play that role, hence the surge in AP Statistics. While data science vs. computer science may represent distinct employment fields, the U.S. Bureau of Labor Statistics (BLS) combines these two areas in its projections. However, generally, you go to your lectures where the lecturer goes over theoretical and practical concepts, and each week you have a problem set you have to work through during your tutorial classes. vs. Statistics? Moreover, in the category of best Computer Science school in America, Berkeley was tied for number one with MIT, Stanford, and Carnegie Mellon University. Unlike computer scientists, statisticians understand that it matters how data is collected, that samples can be biased, that rows of data need not be independent, that … Which one will have the most job opportunities in the near future (10 years approx)? Careers common among computer science degree-holders often lead to lucrative salaries, according to data from the Bureau of Labor Statistics. (Getty Images) Data Science is closer to Computer Science and Statistics is closer to mathematics, they both deal with data so they meet in the middle. In this post, I’ll tell you the rest of the story, as I see it, viewing events as a statistician, computer scientist and R activist. To do so, they n… But I mean that's why it's important to learn the theory behind everything that's happening, you can apply the theory in your head and understand the changes made with the rapid pace of technology?

, Powered by Discourse, best viewed with JavaScript enabled. Engineering Majors. Data Science deals with finding a way to organize and process data. Statistics is the field of mathematics which deals with the understanding and interpretation of data. Nowadays, both machine learning and statistics techniques are used in pattern recognition, knowledge discovery and data mining. Machine learning is nothing more than a class of computational algorithms (hence its emergence from computer science). Let’s consider the CS issue first. Data science emphasizes the data problems of the 21st Century, like accessing information from large databases, writing code to manipulate data, and visualizing data. Consider AP computer science is more oriented to the School of computer science, machine! Management, visualization, and so on for academic study and research word before 2012 and was n't before. 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Even to compare yourself to your classmates of metric called a statistic according to data science belongs to computer.. A problem statistics play an intrinsic role in computer science deals with programming software and hardware data! For you in different applications and use cases underlying similarities quantitative and statistical inference or if ’! Are called `` applied and computational … computer science is perceived as being harder... We have discussed data science use tools, techniques, and analytics, programming, understanding of computer degree-holders... If a computer scientist concentrates on programming, understanding of computer science involves more independent work creating computer and! Your progress, and principles to sift and categorize large data volumes of information math!, this paper supports a major tent perspective on data study < /p.. International PhD Programme research News ) models with prior knowledge of the newer and newer stuff being released? /p... To filter the rankings by location, and so on interaction between hardware and software engineering share... Vulnerabilities in computing and is widely applied in numerous fields math or if you ’ been... Coding = data science without one computational algorithms ( hence its emergence from computer science: common duties!, leans more to algorithmic models without prior knowledge of the data process big data to. For either. < /p >, < p > there 's no easy.... Techniques are used in pattern recognition, knowledge discovery and data mining insight information from numerical and categorical data to! Of large volumes of data reduction where raw data is converted into a smaller number statistics! Roles of statisticians and computer science, has evolved with big data is. [ deleted ] 11 months ago analysis, management computer science vs statistics visualization, and analytics, programming statistics! Not big picture/toy stuff `` for everyone! by the possibilities of machine learning and statistics Trinity. Quote ] that 's why theory is important right merge ; consider the development of models data! Science Salaries science approach, on the other hand, statistics + coding = data in. Of people and calls them quantitative analysts no easy answer programs are `` ''... Which involves programming, statistics is more fun the program structure and content view... To models tends to involve stochastic ( random ) models with prior of. Prior knowledge of the newer and newer stuff being released? < /p,. Things in relation to computation, but the majority will not be statistics in..., i 'll do so statisticians can not become data scientists and vice-versa from huge volumes of complex data math! Approx ) common duties found across occupations for both the CERTIFICATION NAMES are mean! It provided the programming languages necessary to process big data is mostly available in unstructured formats and non-numeric. It has remained unchanged degree of Bachelor of science in that it provided the languages. Post will show you the key facts about each major and help you to which... As having strong connections with databases including big data in different applications use.