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The languages of Data Science

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For anyone just getting started on their data
science journey, the range of technical options

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can be overwhelming. There is a dizzying amount
of choice when it comes to programming languages.

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Each has it's own strengths and weaknesses
and there is no one right answer to the question

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of which one you should learn first. The answer
to that question depends largely on your needs,

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the problems you are trying to solve, and
who you are solving them for.

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Python, R, and SQL are the languages that
we recommend you consider first and foremost.

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But there are so many others that have their
own strengths and features.

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Scala, Java, C++, and Julia are some of the
most popular.

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Javascript, PHP, Go, Ruby, and Visual Basic
all have their own unique use cases as well.

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The language you choose to learn will depend
on the things you need to accomplish and the

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problems you need to solve. It will also depend
on what company you work for, what role you

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have, and the age of your existing application.
We’ll explore the answers to this question

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as we dive into the popular languages in the
data science industry.

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There are many roles available for people
who are interested in getting involved in

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data science.
Business Analyst

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Database Engineer
Data Analyst

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Data Engineer
Data Scientist

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Research Scientist
Software Engineer

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Statistician
Product Manager

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Project Manager
and many more.

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Let’s dive into what we will learn in Lesson
1. We will put most of our focus on the top

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three Data Science languages: Python, R, and
SQL, which each have their own lessons. Then

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we will go on to highlight other noteworthy
languages and what makes them special. Then

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we’ll finish with a short quiz to test your
knowledge!

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● 1.1.1 - Python
● 1.1.2 - R

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● 1.1.3 - SQL
● 1.1.4 - Other Noteworthy Data Science

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Languages
● 1.1.5 - Practice Quiz