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game, who was huge, snatches Dave up by his collar, and the only thing that stops the man from beating him to a pulp, is the look of terror in Dave’s eyes. He looks down at Dave, as a father might look at a child, and gives him some valuable advice:

If you have done your homework, then you know there are basically two programming languages optimal for a career in data science: R and Python. Although R is used among statisticians and researchers, and it can be used for Data Science, Python is by far your best choice.

Apple, which has been ultra-consistent on its data and privacy strategy, is probably doing the right thing, but Facebook and others are doing right by their businesses (and shareholders) in raising the alarm. In the end, though, Apple’s App Tracking Transparency will launch and impact countless developers and millions of users. In the meantime, I expect Facebook and others to start figuring out how to knit a new data sharing sweater.

You have reached a point in your career that it does not make sense to continue doing the same thing. Maybe you are bored, don’t earn as much as you deserve or, like me, simply never liked your job. Amidst a career turmoil, you came across data science and noticed there is a massive opportunity by switching careers. Also, you have found several coding tutorials on YouTube by Data Scientists.

- Monthly membership and a bit expensive: in this category, you can choose from three platforms (DataCamp, Codecademy or DataQuest). All of those platforms offer a Data Science with Python track.

For those with little or no background in programming, Python is the most accessible programming language. It is incredibly easy to learn due to its simplified syntax, which makes coding faster compared to other programming languages, such as Java. This is an advantage as Python allows those who are amateur programmers to read your code and collaborate with you. Therefore, Python can increase productivity and accelerate your career transition.

Because Data Science is a hot topic, multiple YouTubers are offering quick alternatives for beginners: ‘Learn Python fast and easy’ or ‘Pandas in 10 min.’ However, researchers say that the learning process is relatively slow, requires repetition and is most effective when distributed across spacing intervals [1][2]. Therefore, a well-structured curriculum is vital to building a solid foundation in a new skill, such as programming. Also, don’t forget that programming requires both cognitive (new syntax) and motor skills (typing). This means it is practically impossible for beginners to learn Python in a few hours, let alone in ten minutes from watching a video on their mobile phone.

That said, I strongly recommend DataQuest because their lectures are not videos but texts. You have to read and then start typing what you read. It seems a bit old school, but it works really well for beginners, who require more time to process what they are learning. They provide you with the instructions and a script area to test your code on the same screen. Their format is simply perfect for those who are seeking to optimise their study time.

I am sure you have watched a video on how to write a function or a code. But, have you watched it whilst trying to understand the logic behind a code and typing on your keyboard? As Python and functions get more complicated, learning from videos, do not work. As a consequence, you will often have to watch over and over the same explanation, which is less effective and time-consuming. Basically, you will spend a lot of time pausing the video and trying to find the precise minute/second you want to start watching again. This is annoying.

Last but not least, the DataQuest curriculum is created based on real-life data, such as Android