Friday, July 26, 2013

First Coursera Certification







I haven't been writing much lately - more on that another time. My last post talked about my first massive open-source on-line course in statistics at Udacity. It went so well, and I enjoyed it so much, but I still hadn't committed myself to signing up and getting a certificate of completion. I wanted to see what that was like, so in May I signed up for Introduction to Data Science at Coursera. It meant eight weeks of lectures and assignments in a new field.

It's been a long time since I was in school. I finished my last formal degree 21 years ago. I was marching towards yet another one in 2000. I was a course or two and a capstone project away from completing a Masters in computer science when the pilot light inside me blew out. I remember it like it was yesterday: I was sitting in a large lecture hall, listening to a professor drone on about the year long capstone project. I realized that I couldn't do it anymore. The motivation was gone. I stood up, marched over to the bursar's office, withdrew from the course, and never went back.

I've continued to read and dabble on my own, but I haven't done anything formal since then. All my education was obtained the traditional way: take a class in a classroom, do assignments, pass tests, get a grade. I realized that I needed to add more structure to my efforts, but I couldn't go back to the way I've always done it. The rise of Khan academy and on-line courses was perfect for me. I wasn't sure if a new style would suit me, but I was anxious to try. Statistics at Udacity taught me that I could do it. Now it was time to try it out for real at Coursera.

I'm impressed with how Daphne Koller and Andrew Ng are running little experiments on-line to learn about this new educational idiom. It's a challenging problem: How do you handle tens or hundreds of thousands of students in a single course? Lectures, grades, assignments - everything has to be re-thought with this in mind. There were times when mid-course tweaks were added.

The material and assignments were varied and well done. I love Python, the language of choice for all the programming assignments. I have PyCharm from JetBrains. They make the best programming tools on the planet, so my local environment was a pleasure. The grading meant immediate feedback - perfect for an impatient American like me. The variety was wonderful - Python, an online Map Reduce, Hadoop on Amazon Web Services, and data analysis at Kaggle.com. I thought the online materials were very good. Bill Howe did a fine job with the lectures. I could have taken more advantage of the course site and forums, but there are only so many hours in the day.

The course finished during the first week of July. It took a while to sort out all those students, but I finally got my certificate, with distinction, the other day.

I need some time to work on some personal projects, but I've already got my next one lined up. The data analysis using R course that I had my eye on is being offered again in September. I can't wait!

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