Self-Learning Data Science

This vital article serves two purposes: 1) to address a popular misconception in the academic world, and 2) to provide a short list of approaches and resources available to anyone seeking to become competent data scientists.

There is a self-serving conflation advanced by many academicians of degrees with competence. The fundamental idea, of course, is that people who are trained to do things that work tend to outperform those who haven't. The intellectual slight of hand here, however, is that many university programs fail to train students to do things that work. Between grade inflation, outdated curricula, and prolific online resources completely outside of the traditional college system, it has never been easier to develop competence without subjecting oneself to high tuition costs and the egomaniacal antics pervading the collegiate system. This is particularly true for digital domains, including the areas of data science and artificial intelligence.

I have met some extraordinary data scientists without the fancy name letters, and also some real dummies with both Masters and Doctoral degrees.

There are good reasons to get advanced degrees, and some excellent programs (and teachers) out there, but my point here is that everything you need to master data science is available on the internet. To paraphrase the bar scene from the movie Good Will Hunting, there are reasons NOT to drop 150 Grand for an education you could get for a couple of hundred dollars on the internet.

Of course, you need to know where to go. This website, of course, but there are many other places on the internet that offer helpful content, and many times for less than twenty bucks or even free. 

Check out the following free data science courses:

• Udemy
• DataPen
• CodeAcademy
• Silplilearn
• FreeCodeCamp
• DataSchool
• KDnuggets
• 365datascience
• MyGreatLearning
• DataQuest

That should give you a good taste of what's available to support self-learning data science.

This is a great time to be alive.