Best Coursera Yet

I finished my third Coursera course tonight: Data Analysis, eight weeks of learning R and its application to statistics problems. I've enjoyed all three, but this one topped them all. It was a difficult eight weeks. I spent a lot of hours at night after work and weekend time poring over assignments. It's been tiring but worth it. I've remembered the statistics I'd forgotten, learned a lot of new things like generalized linear models, and deepened my knowledge of R. It's exactly what I set out to accomplish when I started taking on-line classes a year ago at this time. I wanted to see if I could adapt to a new style of learning and self-education. I wanted to prove that I could still absorb challenging material. I'm at an age when it's easy to sit back and tell yourself that you already know it all, that you're too old a dog to learn new tricks. Did I still have it in me? I think I succeeded on all counts.

The professor was Jeff Leek, who's on the faculty of the Johns Hopkins biostatistics department. They claim to be pre-eminent in the world, and after sitting through this course I believe them. His graduate students are fortunate.

I've earned certificates with distinction for the two other classes I've taken. I calculated my point totals for quizzes and assignments for 'Data Analysis'. I think I squeezed out another distinguished certificate. I'll have to wait a week or two to see if my numbers match those from Coursera, but I'm confident that it'll turn out well.

I've got a lot of other tasks lined up. I want to take more of these classes next year, but I'm uncertain about what to take. I want to go further with R and statistics, but there's no clear choice listed in the catalog. I might start haunting Kaggle.com and applying these new skills to problems. I've got some development tasks to get back to.

I found out that I'm two speeches away from achieving the Toastmasters Advanced Leadership Bronze designation. I'll fulfill those easily in the next few weeks. That would be three awards in one fiscal year. I'll only have ten speeches to achieve Advanced Communicator Gold and the Advanced Leadership Silver to become a Distinguished Toastmaster. Who would have thought it'd culminate in this when I started in 2008? Maybe I can do it by mid 2015.

I plan to relax a bit over the holidays. It's been a nice way to end the year.

Another One Bites The Dust

I just finished my second Coursera course. It's hard to believe that "Data Analysis Using R" started just four weeks ago.

This wasn't a terribly difficult course, but lecture time added up. The assignments weren't hard conceptually, but I found myself struggling with the API and the docs. "How do I do that?" was a common question. It was easy to think how I'd do something in a language that I knew better, like Java or Python, but I wasn't always able to conjure up the R equivalent at will. I had to do small experiments on the fly to figure out how to make the language do my bidding.

The third programming assignment set was time-consuming. I was behind the eight ball because I was out of town at a family wedding the weekend before it was due. Thankfully we were given an allotment of late days that we could apply as needed. I used up three of them after returning from MN so I could get the assignment in late without penalty.

Debugging in the R environment is crude, reminiscent of the gbd command line debugger that comes with Java. It's a comedown for a person who's used to using the best IDEs in the world to work with Java and Python. I started using the R plugin for IntelliJ for the fourth assignment. I hope they keep expanding and improving it.

R does have some rudimentary object-oriented features, but it's firmly in the functional camp. A friend pointed out that R looks similar to JavaScript. As usual, he's right. I started eschewing the '<-' assignment notation in favor of '=' to make the visual resemblance stronger. The Renjin interpreter makes it possible to run R inside Java. I found out that you can also run R on CUDA. I'm looking forward to trying those packages and seeing what performance benchmarks would look like.

This one was a sprint. The next one, "Data Analysis", will emphasize problems that R is used for, diving deeper into regression and analysis. I'm looking forward to getting back in touch with my mathematics roots. It begins next Monday.