Original subtitles

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Hello everyone and welcome to the lecture discussion on what is data science and this lecture will briefly

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be discussing three main topics we'll talk about the growing interest in data science is a field.

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The growing demand for data scientists in the job market as well as an overview definition of what is

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data science.

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A simple Google Trends search for the term data scientist reveals a recent explosion in popularity for

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people searching for the term data scientist.

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This is because data science can affect so many fields and domains.

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You may already be familiar of domains that work closely if data science such as machine translation

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speech recognition robotics search engines etc..

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However they do science can affect other fields such as biology health care humanities finance Medical

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Informatics business economics and so much more because data science is applicable to so many fields

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of study.

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The explosion of popularity and the ability to use data science has grown just in the past few years

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tremendously.

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Searching for job trends on indeed dotcom also reveals Eytan exploding demand for data scientists in

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the job market.

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Over the past four years there's been a 1600 percent growth in job postings for the term data scientist

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.

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In fact data scientists has been called the sexiest job of the 21st century by the Harvard Business

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Review McKinsey and Company project a global excess demand of 1.5 million new data scientists needed

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.

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This is going to lead to a huge skills gap that you can fill.

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Allowing data scientists the man very generous compensations for their new skill sets.

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The explosion of the popularity of data science can be attributed to many factors but there's four main

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driving factors.

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One is that there's more data being created than ever before.

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The second being large computing power is easily available.

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Things such as Amazon Web Services and Google's cloud computing platform have allowed us to have large

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computing power at our fingertips.

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The third being new programming tools tools such as the our programming language to help you quickly

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analyze data and perform statistical analysis on it.

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And finally this huge skills demand has led to generous compensation for data scientists meaning more

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and more people are willing to jump into the new field will learn a lot and demand those higher salaries

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.

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Now let's talk about a definition of data science we can think of data science as an intersection of

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fields the intersection of computer science math and statistics knowledge and then general domain knowledge

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.

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We can look at the intersection of just two of these fields.

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For instance the intersection of computer science and math and statistics leads the field of machine

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learning.

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You should note that machine learning is not the same thing as data science instead of machine learning

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is part of data science.

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If we were to cross computer science and general domain knowledge of a specific field you would get

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software development meaning use using computer science knowledge develop software very specific domain

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and then if you combine math and statistics with domain knowledge you'll get classic research such as

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research performed in social sciences in academia.

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It's the intersection of all three of these topics where you get data science as an outcome in this

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course.

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You'll learn how to use computer science programming with the R programming language.

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The math and statistical analysis available in our programming language and apply it to various domains

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of study in order to fully understand the full data science lifecycle.

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All right let's start learning all these new skills with the rest of the course.

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Thanks everyone and I'll see at the next lecture