Education is changing and the change is affecting our lives and the way we spend our time. I hardly believe that anyone has never heard about MOOCs, which stands for Massive Open Online Courses. Browsing among the huge offer of courses available online for free is something like discovering a new world.. or several new worlds actually.
In the variety of the courses offered by Coursera I have found utterly interesting the Data Science Specialization offered by the Johns Hopkins University, that entails 9 courses and a final Capstone Project. I appreciate this offer especially because they concentrated several essential information that if you wanted to collect otherwise you should be reading tons of books, web pages, software documentation, probably without finding immediately the connection among them.
With the recent advances in technology, trans-disciplinary concepts such as exploratory data analysis, reproducible research, regression models, machine learning, are progressively gaining importance in several fields and are shaping the "profession" of a "data scientist", a professional with a strong background in statistics as well as cutting edge expertise in technology.
So far I have successfully completed the first two courses, namely The Data Scientist's Toolbox and R programming. Since I'm a lazy person, I need to be motivated, otherwise I'll use the excuse that "I don't have time, I'll do it later". That's mainly why I enrolled in the Signature Track, in order to have deadlines, and eventually I got certificates, and shareable permanent links to course record pages, that look like this and this.
I paused in August and first week of September, and missed the beginning of the other courses, thus I'm starting again in October.
Meanwhile I've found another relevant course, partly overlapping some of the concepts of the specialization, namely Data Analysis and Statistical Inference, offered by Duke University. I'm currently enrolled in this latter, and I found several advantages: it is a lot oriented towards applied statistics and offers tons of practical examples. It also offers an excellent book (free for download, but I bought it due to the ridiculous price - and because I love paper books).
A bonus is that it doesn't require previous knowledge of statistics, which allowed me to brush up my statistics, proceeding quickly through the first weeks of course (I did the first week in one afternoon - OK, I admit it, it took me until 1.30 am).
I'm also watching another course, that is starting at the end of September: it's Mining Massive Datasets, offered by Stanford University. Yes, Big Data. I know it is probably too much in my schedule, but hey, better than mindlessly surfing Facebook in my spare time..
Next time I'll talk about more MOOC platforms and their offers..