XIV Международная студенческая научная конференция Студенческий научный форум - 2022

Machine learning, artificial intelligence, neural networks, speech recognitions and computer vision are not strange words used at specialized conferences. Everything that surrounds us (when we go to school or work, when we fly, when we go shopping) is BIG DATA. Data is our life. And science about this sphere determines our life.

Data Science works with Big Data. Big Data is vast amounts of unstructured information. Man uses mathematical statistics and machine learning to work with data.

Data scientist is an expert analyst who structures and analyzes large amounts of data, applies machine learning to predict events and detect non-obvious patterns, helps to create and improve products in business, industry and science.

History of Data Science

In 1962 John W. Tukey predicted in his paper “The Future of Data Analysis” the impact of modern electronic computing on data analysis as an empirical science. Publication of this scientific paper was considered as the beginning of the history of Data Science. This term was widely used only in the 1990s, and became generally recognized only in the early 2000s. Specifically, in 2002, the Data Committee for Science and Technology began publishing the CODATA Data Science Journal, and in January 2003, the first issue of The Journal of Data Science at Columbia University was published.

General interest in Data Science can be traced back to the Gartner hype cycle for emerging technologies. Data science, subdivision of Big data technology, appears on that curve in 2011 (see picture 1). Since that time everyone has been talking about big, really big data, and about those who are in charge of proceeding this information (see picture 2).

Picture 1

Picture 2

Demand

Data Scientist is a fairly popular profession. In 2016, a ranking of the 25 best vacancies in the United States was published by the American company Glassdoor. In this ranking the profession of Data Scientist topped the list. Since that time highly educated specialists have always been in demand.

So far machine learning algorithms have been developed rapidly, predictions based on them are getting more accurate, and there are more and more areas for their application. Therefore, the profession of Data Scientist has a great future. In Russia, the demand for these specialists is also constantly increasing. For example, in 2018 there were 7 times more vacancies with the title Data Scientist compared to 2015, and growth continued in 2019. In mid-April 2020, hh.ru had 323 vacancies with Data Scientist in the title. Most of them, of course, are in Moscow-204 and in St. Petersburg-39, the rest of the vacancies are scattered in other cities.

Scope of application

The scope of application areas for Data Scientist is very large. For example, there are such options as banks, business, IT-sphere, transport companies, insurance companies, medicine, bioinformatics and modern genetic research, physical research. This is just a small part of the list. Experts in Big Data are irreplaceable wherever you need to assess risks, make predictions and conduct deal.

Necessary skills

Critical thinking is a crucial personal quality in Data Science. Knowledge of algorithms and data structures, development of machine learning algorithms, which consists of math, theory of probability, mathematical statistics are also highly required in machine learning. This sphere also claimssuch an important skill as being a team player, because that makes it possible for each data scientist to easily communicate and cooperate with specialists from other areas.

Study

Nowadays there are various opportunities to get the required skills – not only by obtaining a university degree, but also as a part of special short-term courses. The list of the best universities, where people may get the education in the sphere of Big Data, is presented below.

In Russia:

High School of Economy

Moscow Institute of Physics and Technology

Skoltech

Innopolis

Moscow State University

School of Data Analysis

In Great Britain:

University of Cambridge

Imperial College London

King’s College London

In Europe:

Technical University of Munich

Delft University of Technology

University of Amsterdam

In USA:

Cornell University

New York University

University of Southern California

In Canada:

University of Toronto

Conestoga College

Humber College

Now we can draw a conclusion that Data science is a big part of our world. Professionals in this area will be in demand for a very long time. Not for nothing, Harvard Business Review journal called this profession the sexiest job of the 21^th century. There are many possibilities to study this major. In addition, this job is really well-paid. Data scientists have flexible working hours. Contrariwise, the profession of data scientist is very complicated, it requires a lot of knowledge and time. Nevertheless, it is really worth it.

source links:

https://datascience.codata.org/

https://www.gartner.com/en/research/methodologies/gartner-hype-cycle

http://www.jdsonline.com/

https://www.historyofdatascience.com/

https://www.forbes.com/sites/gilpress/2013/05/28/a-very-short-history-of-data-science/

https://www.oracle.com/ru/data-science/what-is-data-science/

https://www.sas.com/en_us/insights/analytics/what-is-a-data-scientist.html

https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century

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