Francisco Lobos
Versión en español: Tomé un MOOC

I took a MOOC

A couple of weeks ago I finished Computational Molecular Evolution, a MOOC (massive open online course) in Coursera taught by Anders Gorm Pedersen from the Technical University of Denmark (DTU). I joined it because I wanted to review some concepts related to phyloinformatics learnt during my undergraduate years. This is the first course of this kind that I took and have been very satisfied with it, so I thought it would be nice to share my impressions:

  • Despite being the first one, I consider this course an example of a well-executed MOOC. Professor Pedersen showed a good understanding of the subjects, which was reflected in the clarity of the explanations.

  • The use of a virtual machine with Xubuntu was a great idea, allowing the standardization of the exercises and letting us work like the experts do in real life. Too bad that one of the programs used (PAUP) is paid, although there are free alternatives, such as MEGA and PHYLIP.

  • Each practical quiz was conceived as a step-by-step tutorial, explaining the meaning of each command and its theoretical background. It was noticeable the fact that these exercises were previously tested and polished, which I appreciate, since I had no difficulties to follow them.

  • I wish the course had covered more topics (bootstrapping, for example), although I think that the content selection was accurate and covers the topic of computational phylogenetics fairly well.

  • The topics were covered with an adequate depth. However, I would like recommendations of scientific articles related to the theory or application of the subjects discussed in the lectures. Some of that was shown in the lecture about reconstruction of ancestral sequences.1 I understand that maybe it wasn’t one of the main objectives of the course, but I was left wanting more. It would have been nice to know some real life examples. For instance, nothing was mentioned about computational phylogenetics in a clinical or epidemiological setting.2 It’s not a serious issue, but I would have liked to see it on the course. Call me picky if you want to.

At the time I enrolled at the course I was afraid that the course would be difficult or it would require a lot of time, which would had forced me to abandon it. Fortunately, that idea never entered my head. Instead, each week I was glued to the monitor watching the lectures, while concepts that previously were hard to assimilate became familar to me. At the end of last quiz I found myself wanting more, something that few classroom courses managed to achieve! I can only thank Professor Pedersen and the staff from Coursera and DTU who made this course possible, for sharing their time and knowledge.

Clearly this MOOC set the bar high for future courses of this type I intend to take. In fact, I already took two more, related to biostatistics: Case-Based Introduction to Biostatistics and Biostatistics Mathematical Boot Camp 1. They will probably be more difficult than Computational Molecular Evolution, but that’s a topic for another post. Maybe.

  1. Even giving examples outside the biological field, such as the inference of original manuscripts. 

  2. This article by Carl Zimmer in Wired last January comes to mind. It’s about a carbapenem-resistant Klebsiella pneumoniae outbreak in a hospital.