The demand for skilled developers of data science continues to increase. If you want to work in this area, these are the things you need to learn.
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The demand for skilled developers of data science continues to increase. This is what you need to learn to have a solid career in this industry.
Want to expand your skills in the field of high technology? According to Shu Wu, Director of Indeed Prime said: 'The demand for recruiting developers with data science skills is huge, along with the outstanding growth over the past 4 years in science-related recruiting jobs. data (data science) ".
Director Shu Wu said: 'The prospect of this job is huge, data science is an attractive salary but fierce competition. A data scientist is great if they are experts in data validation, but the person who can make 'easy to digest' data in the entire organization is the pinnacle. "
Karen Panetta, an IEEE member and head of the high-tech department at Tufts University, said: 'Technological advances and huge online data volumes are affecting each field and have an impact. big to the economy. This is referred to as 'data storm', not only because of the huge amount of data, but also due to the speed of change, growth and the variety of data available . "
Karen Panetta adds: 'Knowing how to use a traditional spreadsheet and database will not be enough in the emerging Big Data revolution. The analysis needs to be completed in real time, when decisions can be affected. Knowing how to use software tools is only part of this challenge. Understanding data in many fields, being able to convey its meaning and being able to use statistical data will be different from traditional figures' .
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In terms of learning programming languages that allow you to work with data, 'the standard for any language is to find something and do it right away , ' said Forrester analyst Mike Facemire. Code writing is when you do something wrong, you will have great experiences . " Facemire recommends visiting Github to see examples and search for a data set that is interesting to you and learn how to analyze it.
Facemire said: "After all, the more important thing is to understand how to solve the problem by breaking it down into smaller problems than knowing its language. After all, it's just a way to interact with The computer does not care what language you are using, it is more interested in you breaking down the problem properly and resolving it properly to have a good result ".
"Some educational institutions have created data science programs, including Northeastern University, Boston University, CUNY and Merrimack College. Some schools also offer online courses, programs and programs. The seminar is low-cost through the IEEE Computer Association, "Panetta said.
If you want to pursue a career in data science, you should consider learning one of the following three languages:
1. R
"R is a language and framework used by data miners to develop statistical software and data analysis , " Panetta said.
This language has experienced tremendous growth when analyzing data and data science has become more popular in recent years. However, its popularity has decreased slightly. R has tools built for data scientists with specific extensions and plugins for that purpose.
Panetta said: 'The important thing when learning languages like R is to understand basic math skills. It would be a disaster if we only believe in the results of the software without knowing what we are measuring and not understanding the input data we provide. '
2. Python
"Python is a powerful, multi-purpose programming language and includes tools that can be applied to environments that require visualization that can appear on web pages or on phones. It is also easy. Read more R " , Facemire said.
If you are in the moment of thinking about your job, "I want to be a data scientist - what language should I learn?" Consider both R and Python and see which language is right for you. Both are feasible. Businesses will often not prioritize any language when considering the skills of a data scientist.
See also: What is Python? Why choose Python?
3. Java
The recent Java programming language is ranked one of the most popular and versatile languages to write, based on a survey from WP Engine. It is also a multi-purpose programming language, specifically designed to be as less dependent on implementation as possible. It can be used to build everything, especially scalable platforms, multithread platforms, and a powerful user platform.
"Java is the interpreter language - unlike C and C ++, Java does not require low level hardware knowledge , " Panetta said. That helps those who are studying outside the field of computer science and technology more accessible to Java. According to Indeed, Java is also the most requested programming language in technology postings.
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