MOOC status, November 2014

Hi.

Yeah, I know, I haven't kept this very well-updated. But let's see... The last post was just about two months ago. What's happened since then?

I've (successfully) finished the following courses:

• Introduction to Systems Biology - Mount Sinai
• Introductory Human Physiology - Duke
• Statistical Inference - Johns Hopkins
• Dinosaur paleobiology - U. Alberta (well, the course is still running, but I've done all the activities, so I'm done with it)

I've dropped the following courses:

• Fundamental of Neuroscience part 2 - Harvard
• Musculoskeletal Anatomy - Harvard
• Data Analysis and Statistical Inference - Duke

I have started the following courses (some of which weren't quite planned for):

• Immunology part 2 - Rice
• Astrophysics part 3 - ANU
• Exploring Neural Data - Brown
• Experimental methods in systems biology - Mount Sinai
• Functional Programming - Delft

By and large, I won't be starting any other "Big MOOCs" this year. I am considering signing up for The Neuroscience of Vision from MIT, as that's a short, 4-week course. If it's too heavy-going, I can always drop it - I find I am increasingly doing that kind of thing: sign up to a course to give it a go, then drop it if it doesn't quite fit what I want, or if it really doesn't fit in my schedule.

All in all, that's 29 courses I've finished. 11 are biology / life sciences, 9 are statistics / data science, 5 are regular computer science, the rest are a smattering of economics, physics, humanities, etc. By the end of the year, barring disasters I should have at least five more.

I'll do (maybe) detailed writeups of the courses I finished, so let's just do a quick recap of the ones I dropped:

• Neuroscience from Harvard: this course is actually pretty good and has some stunning graphics. Unfortunately, the focus is very much on visuals, animations, etc. It certainly works for some. As for myself, I really can't find it in me to watch cartoons about house parties as a metaphor for the synapse.
• Musculoskeletal Anatomy: I don't what to think of this one. Either the course runners are incompetent and/or have lost interest, or something terrible has happened (like a disease, an accident, something). The first couple of weeks were pretty sleek, with professional-looking videos. It's gone downhill since then, the syllabus has been truncated (each week was initially supposed to finish with a wrap-up about the "case" under examination), the content is released late and only consists of pages of text, the quizzes have glaring mistakes that are not corrected, all the professors and TAs have fled the forums (not a single post from a member of staff in over three weeks). It looks like they're scrambling to put up some content every week but are improvising with very limited resources. It's the first time I drop a course when it's almost over, but I find I can't find the motivation to keep going. It feels like standing on a sinking ship.
• Data Analysis and Statistical Inference - I've dropped this one purely for scheduling reasons. It's a very good course, perhaps too introductory at times for me, but it broaches many subjects like ANOVA and such. The course is offered again next March, so I'll be taking it then.

As for the current ones:

• Immunology is hard on memorization, but very interesting and the professor is great. We're onto T-cells now, pretty complicated stuff.
• Astrophysics is a lot of fun. Dabbling in relativity and quantum mechanics without the hard-core maths. It's actually pretty relaxing.
• Exploring Neural Data is a pretext for doing scientific computing in Python (instead of R, for instance). The lectures are engaging and the assignments are pretty thorough. Unfortunately, it's rather short: there's only a unit every other week, to accommodate students without a programming background, and so there are only 5 units altogether, each with an assignment that takes me, I don't know, a few hours to complete. So it stays pretty basic.
• Experimental Methods in Systems Biology - a follow-up to the Introduction to Systems Biology class. It's the part I am the least interested in of all the Sys Bio courses, but it's an understandably requirement to take them all. Anyway, it's a description of the major technologies used in major biology labs today: Illumina sequencing, mass spectrometry, etc.
• Functional Programming - I didn't plan on taking this one - I mean, functional programming is fun but I've already dabbled in it (and still do in a limited way, thanks to Java 8 streams). Simply I chanced on a video of the professor, who is kind of a heavyweight in the field (used to be a principal scientist or something at Microsoft Research, author of a ton of papers, etc. - still an open source fan, as far as I can tell, despite having worked at MS) and decided to take it just for kicks.