General, Research, Technology

Is it possible to become a data scientist? We dispel myths and fears about the profession

When it comes to working with big data,many immediately imagine academics in some research institute or programmers sitting at a computer and writing code 24/7. Therefore, it is believed that mastering the profession of a data scientist is not easy (it is not just that it is called one of the most demanded!). But in fact most of what you know about Data science - it is a myth. Let's analyze the most popular ones.

Many people are wrong about Data Science

Content

  • 1 Data Science is only machine learning
  • 2 To work with data, you need to be a programmer
  • 3 Data Scientist is boring
  • 4 Data Science doesn't apply in everyday life
  • 5 It's too late to learn to be a data scientist

Data Science is only machine learning

It is widely believed that data scientistsall they do is develop neural networks and do machine learning. This is not at all the case, data science is much more extensive than it might seem at first glance. Data Science is more about data analysis, while another branch of data science, Machine Learning, is responsible for machine learning. Data Scientist is bigger processes data arrays, looks for patterns in them and helps to solve various problems in business with their help.

For example, using such an analysis, you can identifywhere does the bank's client spend the most in order to provide him with an exclusive individual offer next month. And to automate this process, you need machine learning specialists who can teach computers to make automatic predictions. And all of this combined is Data Science.

To work with data, you need to be a programmer

Shot from the series "Silicon Valley"

Data science - a new specialty, and it does not have anyrestrictions on who can learn from it. Whether you are an engineer or a humanist, it will not be difficult to understand big data. The main thing is to find the right course, where you not only need to study textbooks, but there are many practical tasks and support from teachers (mentors) who will help if something does not work out.

And, of course, have the desire to learn and learnnew. Of course, if you know programming languages ​​and communicate with a computer on "you", it will speed up the process of mastering the specialty, but often having another education not related to programming can be a big plus. Financiers will be able to solve problems related to their specialization with the help of Data Science, and biologists will be able to make new medical discoveries.

For example, not so long ago, the DеepMind team createdthe AlphaFold 2 algorithm, which helped determine the three-dimensional structure of the protein. This discovery will allow the creation of new drugs for diseases, because with the help of the structure, scientists will know how the protein works, how it folds and interacts with other elements so that it can be used painlessly in drugs.

Data Scientist is boring

The typical data scientist in the eyethe majority looks like a skinny guy with glasses who works from morning till night with tables, builds diagrams and counts, counts, counts. The same stereotype was previously applied to programmers, but everything has changed. It is enough to watch the series "Silicon Valley" in order to at least superficially understand what tasks data scientists face in the modern world. These are not just office clerks who copy data from one spreadsheet to another - they often face tasks that no one else has solved. And they reveal patterns that a simple layman in life would not even notice.

For example, by analyzing meteorological data, you can predict not only when it will rain, snow or hurricane, but oil prices, in order to subsequently apply the obtained data on the exchange. Not everyone can see such a pattern.

Who would have thought that studying the weather could predict oil prices?

Data Science is not applied in everyday life

Another myth that formed whenthis profession was just developing. Then, indeed, all calculations remained mostly on paper. But then, when the business realized how important data was, everything changed. Nowadays, you see data scientists working every day without even knowing it. For example, when you go to a social network, a block with the accounts of people you may know is displayed there. Or choose new categories of cashback in the banking application. Or when you call a taxi, and the system selects the driver closest to you according to your requests from dozens of others in the area.

Machine learning through the consumption of a large number of images makes it possible, for example, to successfully implement the Google self-driving car project.

It's too late to learn to be a data scientist

Shot from the film "Trainee"

No, the big data market is growing with everyyear. In this regard, the demand for specialized specialists is also growing. So you will not even have time to just jump into the last car of the departing train, but calmly walk to the locomotive and make yourself comfortable.

Data Scientist salaries only grow

Moreover, to study for 4, 5 or 6 years in order tothere is no need to become a Data Science specialist. The Data Science course at SkillFactory, which lasts 24 months, teaches this profession from scratch, and is suitable for both newbies and existing programmers.

Course students not only learn the basics of working withbig data, but also Python programming, the basics of mathematics and statistics, master practical machine learning and data engineering. The program is compiled by leading experts in Data Science - NVIDIA and EORA. The benefit of this course is also that it covers the main areas of work with data. At each stage of the course, you will solve real cases that will become part of your portfolio. Mentors will help you get to the end of the training, always keep you motivated and help you if something is not clear.

Hi-News.ru readers can get 50% discount per course * by promotional code Data Science until December 25, 2020.

Considering that within a year or two after the start of studies, you can get a job as a junior with a salary 80-120 thousand rubles, it is better not to miss this opportunity. The demand for data scientists is growing almost every month, especially in a pandemic when the IT sphere is on the rise and needs new staff.

* Discount cannot be combined with discounts on the website