Python: the best language for a data science job? (2018)

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You want to get into data science and aren’t sure if you should learn Python?  Watch and read here to find out if you should learn Python, how to access it, if snakes are involved, and free or cheap learning resources you can use if it is right for you.

If you want to get a job in data science check out our free guide to getting a job in analytics and make sure to subscribe to get all future content.

Python is really hot these days.  It makes sense that an easy general purpose programming language with data science capabilities would be popular.  But is that where you should start?

Who should learn Python:

Anyone who wants to work in data analysis should consider learning Python.  Python jobs have grown through the roof, and it is capable of doing just about anything.  Python is especially useful when you need analysis of web data, so if you are looking for a job at Facebook or Google it might be your best place to start.

Advantages

The biggest actual advantage of Python is that it is probably the most versatile programming language on the planet.  It is a general purpose language with analytical capabilities.  That means it can do just about anything: you can write a video game, you can build a website, or you can develop an analytical dashboard.  Or you can write a video game about designing  websites that feature analytical dashboards.

Python was also specifically designed to be easy to learn and easy to troubleshoot.  It is as beginner friendly as languages get.

Python is easily incorporated into web services through its ability to call directly through C, C++, and Java.

And finally, Python is named after Monty Python.  Seriously.

Disadvantages

I had to google disadvantages because it truth there are not many.

The biggest disadvantage, and this can be a big one depending on what you want to do, is that it is weak in mobile computing.  One of the only things you cant do in Python is build an IOS or Android app.

Python can also be slow depending on the use case.

All in all, with the many advantages and relatively minor drawbacks, it is easy to see why Python popularity has exploded in recent years.

How to get it

There are lots of ways to get Python because it’s free.  That’s right, just like R it is an open source language with lots of open source development environments.  Which one to get?  Well that depends on how you want to learn Python.

How to learn it

There are lots of free resources out there, but I recommend paying for one.  The reason is that you will find higher quality instruction with all the resources in one place.  The course I recommend is something that I am personally taking.  The instructor is a real world practitioner with 17 patents to his name from his time at Amazon and IMDB.  And best of all, I negotiated a discount for analytics dude followers where you can get it for only $10.  It’s a 12 hour class from an expert instructor for $10, cant beat that.  I don’t get a dime from that, it is purely a discount I negotiated for you guys.  Here is the discount link: Data Science, Deep Learning, and Machine Learning with Python

So should you learn Python.  Well that depends.  Are you learning something to help get a job?  Python is a great language for that.  Are you trying to build something to use on a web app or are looking for an easy way to experiment with machine learning?  Python is probably the right answer for you.

Are you trying to do hardcore statistical research and analysis?  R is the best choice.  You want to be an analyst at a Fortune 500 company, SAS is your best option at the moment.

If you liked this video please hit like, and share it with your friends.  Please subscribe, and until next time I am EW Hulbert, the analytics dude, and thanks for watching.