Many believe that now the Data Scientist profession is one of the most attractive, promising, and highly paid ones. All large organizations have previously created departments for processing their data and are turning into data-driven company’s right before our eyes, which require more and more data specialists.
To become a sought-after specialist in this area, you will require a good understanding of programming, mathematical statistics, and ML. You can get the necessary experience and abilities at some universities, try to pump it yourself, or get it in various courses – for example, on the Data Scientist course at the SkillFactory online school, where you can master this interesting profession from scratch in 12 months.
The Data Scientist’s path is long and those who want to learn need to prepare to go from the initial “I don’t know anything” to the moment when it will be possible to say with confidence: “I solve ML problems and I understand where to apply it plus how to develop more.”
But what is Data Science?
The mention is now heard from every iron. Probably, everyone reading these lines heard something about it.
But what is it?
Someone says that this is another buzzword, which has become so ubiquitous and vague that it has lost all meaning.
There are also claims that Data Science is just a marketing term, which replaced the usual statistics, as ML replaced Data Mining.
The term began to be connected so widely that it became the object of memes and various jokes, like:
- “It is a statistiian who lives in San Francisco.”
- “It is statistics on Mac”
So what is Data Science?
It is the way to think and work with data. It’s regarding taking a scientific approach to working with it. Everything else – programming, statistics, ML, neural networks – are just means.
Data is electricity
Andrew Ng believes that AI is the new electricity, but in reality, “electricity” is data that is now being collected everywhere and applied for a variety of purposes. Including training AI.
We have long been accustomed to the presence of current in outlets and therefore do not pay attention to the electricity itself, but only to the devices that it powers.
For such cases, there is a special term – commoditization (commoditization) of goods/services/technologies, when a product from some brand category goes into the category of ordinary products (commodity). This happened with many services and goods: computers, cars, mobile phones – now they have become comparable in characteristics and we take them for granted. Earlier, people began to perceive electricity as well, and now the same thing has happened with data. Their use has become the norm. Therefore, people are now focusing on the next innovations that will be made possible by the availability of data.
It is the solution of specific and focused tasks that allow a wide variety of companies to achieve profit optimization, cost reduction, increase in revenue, and operational feasibility. Data-Science UA is becoming a generic term focus on solving difficulties in specific administration areas.
Perhaps in a few years, the term will cease to …….