The languages of Data Science
For anyone just getting started on their data science journey, the range of technical options
can be overwhelming. There is a dizzying amount of choice when it comes to programming languages.
Each has it's own strengths and weaknesses and there is no one right answer to the question
of which one you should learn first. The answer to that question depends largely on your needs,
the problems you are trying to solve, and who you are solving them for.
Python, R, and SQL are the languages that we recommend you consider first and foremost.
But there are so many others that have their own strengths and features.
Scala, Java, C++, and Julia are some of the most popular.
Javascript, PHP, Go, Ruby, and Visual Basic all have their own unique use cases as well.
The language you choose to learn will depend on the things you need to accomplish and the
problems you need to solve. It will also depend on what company you work for, what role you
have, and the age of your existing application. We’ll explore the answers to this question
as we dive into the popular languages in the data science industry.
There are many roles available for people who are interested in getting involved in
data science. Business Analyst
Database Engineer Data Analyst
Data Engineer Data Scientist
Research Scientist Software Engineer
Statistician Product Manager
Project Manager and many more.
Let’s dive into what we will learn in Lesson 1. We will put most of our focus on the top
three Data Science languages: Python, R, and SQL, which each have their own lessons. Then
we will go on to highlight other noteworthy languages and what makes them special. Then
we’ll finish with a short quiz to test your knowledge!
● 1.1.1 - Python ● 1.1.2 - R
● 1.1.3 - SQL ● 1.1.4 - Other Noteworthy Data Science
Languages ● 1.1.5 - Practice Quiz