Understanding Data science is becoming one of the most demanded skill sets in the 21st-century job market. Data are flowing everywhere in ever-evolving magnitude. Storing them is costly and business better find ways how to turn them into profit. In some industries, the so-called ‘trickle-down’ effect is slowly observable, as medium-sized companies are now trying to surf the Big Data & Data Science wave and follow suit.
The reality is that without a solid scientific background and some experience with quantitative methods, the vision of becoming a good data scientist can be slightly utopian. With the term ‘Data Science’ topping buzzword charts, it was only a matter of time until smart marketers mined its potential. As a result, the internet is full of Data Science resources with various degrees of quality. Below, we have listed just a few that we use to brush up on methods & techniques, or recommend to students and enthusiasts:
Coursera – Machine Learning with Andrew Ng
With over 2 million people enrolled already, this free online course quickly became a classic amongst those trying to get into Machine Learning. Offered through Stanford University and tutored by Andrew Ng (founder of the Google Brain project)
Udemy – The Data Science Course 2019
A good starter pack for fresh-faced Data Science enthusiast. The course covers the field broadly but does not shy away from the math underlying the discussed concepts, which often the problem elsewhere. Especially cash-cow resources are trying to sell the idea that you can advance in the field without a proper understanding of the technicalities, which is shameless sugar-coating for profit.
Provides good quality educational videos freely available on Youtube, which cover everything including detailed statistical nitty-gritty in a comprehensive way.
Other sources for inspiration:
Bayes theorem explained through the caveman statistician.
• https://www.dataquest.io/ Offers a set of more specific courses. They offer a free account, but if you want to access some of the niche materials, you need to pay.
• JT Kostman’s Advice for New data scientists
• Jake VanderPlas: Python Data Science Handbook free online https://jakevdp.github.io/PythonDataScienceHandbook/