Virology I: How Viruses Work (11 weeks)
Offer by Columbia University, Prof. Vincent Racaniello
Review: ***
First off, I need to preface this commentary by saying I have not taken a biology class since high school (many years ago) mainly because biology does not really interest me. I am not stimulated by all the labeling and memorization one needs to do, nor the tiny details of which particular proteins need to bind together to make a system work properly. That being said, why would I choose to struggle through 11 WEEKS of essentially just that?! Initially I thought the course was going to be about the vectors and transmission of viruses with maybe an overview of how viruses work (apparently that is for part two). By the time I realized what it was not, I felt I had already invested so much time and energy already that I might as well try to stick it out and finish the course.
So I made it through and learned some interesting things I did not know before but it has not made me into a biologist nor a virologist, nor has it instilled any desire to become either. The class was good though tedious at times for a math-type person. There was one part in the second week where a Poisson distribution was used in determining the multiplicity of infection and I wished that the professor could have continued with more examples and other distributions. The slides and lectures were good, despite having to stop a lot of the video lectures to write down the processes that were new to me. I did not really utilize the discussion boards as I did not have that much time (and interest, if I am being honest) to commit to this class. This is perhaps more information about virology than a biostatistician, with an epidemiology bent, needs to know.
Computing for Data Analysis (4 Weeks)
Offered by Johns Hopkins Universtiy, Prof. Roger Peng
Review: *****
I am just loving every class that Johns Hopkins is offering on Coursera. This was by far the hardest and shortest MOOC (massive open online course) I have taken and I think I just got by the skin of my teeth (feel like I scrapped by) even with a 92/100! I have only worked with R for a year, being mostly a front-end user and this course turns you more into a programmer of R. The concepts were not difficult but implementing them for the assignments were tough, especially for week 3 where it was all about loops. My only other experience with statistical/mathematical programming languages have been SAS and Matlab (I wouldn't really include Minitab in that set). The hardest part was knowing what I may have been missing (i.e. a particular line of code) but not knowing how to articulate that in R or not knowing what to look for on the online resources. The discussion boards were the greatest help. For someone of my skill level, I feel like I need a workbook to go through more examples/data sets and be quizzed on my understanding of the various lines of code. This is not something that the course needs to do but is a niche that could be filled in the publishing world. Or perhaps I just need to go through "Complex Surveys: a guide to analysis using R" by Thomas Lumley and "Discovering Statistics Using R" by Field, Miles and Field.
I have given this five stars because it has shown me what I need to focus on more if I am going to take biostats to the next level.
Mathematical Biostatistics Boot Camp I (7 Weeks)
Offered by Johns Hopkins University, Prof. Brian Caffo
Review: ****
If you have previously taken a course in Probability and Statistical Inference, you should have no problem with this course; it might even be a nice refresher. This course assumes (and states) that you should understand multivariate calculus and basic probability before enrolling. There should be an emphasis in the title on the math and statistics part as the lectures covers primarily these topics, with the bio part being used in some of the examples. The course provides more of the core statistical bases that are used in the field. I don't think I have a single complaint about this course; now I just wish my brain were as great at understanding all the concepts as some of the individuals who were able to elucidate on the discussion boards!
Cased-Based Introduction to Biostatisitics (5 Weeks)
Offered by Johns Hopkins University, Prof. Scott L Zeger
Review: ****
This class is a light, easy-yourself-into-the-field course on biostatistics that is quite opposite to the Boot Camp class listed above. It touches upon the stats but is no way heavy on the math. As the title states, the course relies heavily upon cases to illustrate the key topics and methods and lightly uses the statistical program R. The programming used in the lectures does not differ greatly from what is needed to complete the quizzes; certainly less stressful than "Computing for Data Analysis"! Also provides a great refresher on probability, on the light side.
And now a light distraction with Tom Mison in Sleepy Hollow! So much more delectable than in Lost in Austen...blondes just don't do it for me.
If I am really luck, or efficiently diligent, I will also post a list of recipes to get through and even finish off the Vogue dress. Technically there are two dresses, same pattern, just slightly different fabric and alterations made.
But tomorrow I will make Whiskey Bacon and my first White Chip Macadamia Nut Cookies!
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