Upd

I haven’t posted anything for quite a while, but actually I keep learning. It’s always somewhat sad to see these abandoned blogs created for peer-learning with a couple of posts and then no updates, so you just don’t know if their authors are still learning or gave up on it. Well, I haven’t. True, I’m more into platform MOOCs at the moment, so I’m not using this blog for peer-learning purposes directly. But I generally like this international open peer-learning project and I’m going to update this blog from time to time.

There’s a good occasion for this post: I’ve just completed An Introduction to Interactive Programming in Python at Coursera. I’ve finally done it having failed two previous attempts. It was challenging and I’m not sure I’d have made it if I hadn’t done some preparational job at Codecademy and with the help of Zed Shaw’s ‘Learn Python: The Hard Way‘ (a great educational project by the way).

Just for show, here are the links to the mini-projects I completed during the course. I’m providing the links to my code in Codesculptor, an online application created by one of the instructors for writing and running Python code. In case someone wants to have a look, the best way to do it is by using Chrome (using Mozilla and other browsers may lead to some bugs).

This is actually the first part in Fundamentals of Computing specialisation. Next course in this sequence, Principles of Computing, is going to start in February 2015 and I’m totally going to try it. Before it begins, I’m going to have some fun at Khan Academy.

Finally, some courses I’d like to have a closer look at at a certain point. Maybe someone will find them fascinating as well. If somebody has already dealt with some of them, it would be great if you shared your opinion.

Big plans for my 2nd semester

As the previous experience has shown, it’s hard to cover more than one course in one semester (this way of measuring my learning time seems most appropriate), if you have to work at the same time. Or rather one course and a half. Last semester, these were an introduction to statistics and a bit of R. Initially, I had huge plans for the upcoming semester. While learning statistics and earlier some Python basics I got a bit tired of constant guesswork and having to learn separate pieces of underlying fundamentals, without getting the whole picture. So I totally felt like taking two basic courses in this semester, namely some refresher in math and some intro to computer science.

As to computer science, I really liked the description of CS50, a Harvard CS course by David Malan, which has its online representation both as a static archive and as a MOOC at edX.org. The thing is that:

  • it lasts 10 weeks
  • it has 2 lectures every week, about an hour long each
  • it has 1 seminar a week, about an hour long
  • it includes 9 problem sets, estimated completion time 10 to 20 hours each
  • it includes 1 final project

Well, that’s definitely not what I’m likely to be able to cover before summer, especially if it is combined with a math course. Time for tough decisions. After some hesitation I decided that math comes first:

  • as a more basic subject
  • the thing I really needed while learning stats
  • more realistic to complete by the end of this semester.

There are actually two courses that seem quite appropriate for my needs (and I need to refresh some real basics):

I’m not sure about the latter, but Precalculus looks very promising in terms of at least answering some unresolved questions (simple, but very annoying) I already have after dealing with statistics.

So that’s what going to be my core subject for the semester, just like Statistics was last semester. Now, what about the remaining ‘half a course’ to complete my schedule? Well, I failed to complete Data Analysis last semester and I also want to have some revision of what I learnt about statistics last year. That’s what I think I’m going to be dealing with for the rest of my learning time. Stanford is offering a course in statistical learning (as far as I understand this stands for statistics combined with some machine learning approaches). I hope it won’t be as challenging as it could be after I have acquired some basic skills in handling R (and this course is based on R).

So these are my one and a half courses I’m going to take in this semester. As to CS, I do hope to take it in the summer.

A couple of links for those who also might need some school math refresher: