I didn’t mention that I got my grade on the Coursera Model Thinking course. As I have previously I really enjoyed the class. I highly recommend this course to anyone that uses mathematics to model. It is an eyeopening class!
I really enjoyed this course. I was introduced to some tools I already use like shiny, and others that I have never heard of like yhat. This is a valuable course that I think will change over time as data science developers create more products. I highly recommend this course to anyone.
I received my statement of accomplishment for the Coursera Practical Machine Learning course taught by Johns Hopkins University.
I really enjoyed this course. I enjoyed learning the modeling techniques. I was a little disappointed with the treatment of forecasting. The professor had a lecture on it that said when modeling things that involve time there are different steps to take but that is the subject for another course. I was hoping for more. I have been slowing reading the online textbook they recommended which has been interesting. I am an auditory learner so listening to the lecture would stay with me longer.
I highly recommend this course to anybody. I hope to use the knowledge gained in a side project that I have brewing.
I have been late in posting I received my grade for the Programming for Everybody course. This was a good class and I would recommend it to anyone who wants to begin their journey into the world of computer programming/data science.
I was in the process of cleaning up my package for submission to CRAN when I learned that the BLS has released v2 of their API service. This version requires a key but allows for more requests plus annual average calculations which is cool.
I was shocked and gratified to see that under the Sample Code: R page they were featuring my work with this acknowledgement:
My submission to CRAN has not accepted yet, but I’m still working on it. In the mean time it is available through GitHub.
I’ve wrapped up the Regressions Model course taught by Brian Caffo of Johns Hopkins University. This is my second course taught by Prof. Caffo and I am quite optimistic about this class. He released some new recordings of the lectures which were a lot better production than the earlier ones. I learned a lot from this course and completed the course with distinction
I also have been working through the Programming for Everybody (Python) course which has been a good class. As I have previously written on, I believe programming languages are tools and you should pick the tool that is right for the job. I felt that with all this time focused on R my Python skills could use a little work so I took the course.
One of the key things I took away from the class is the computer science jargon. I knew the concept but expressed it in non-technical terms. Now I can use the terminology my friends in the CS field understand.
I just received my grade for the Coursera Statistical Inference course.
This course was not my first one in statistical inference nor will it be my last. This course was taught by Brian Caffo and I feel he did a good job. I know some students in this course had difficulty with his lectures and what is presented. I think the difficulty lies in the presentation style. Some of the easier material is presented in depth and then he brushes over the middle ground and highlights the point that he feels are important. It is a lot of material to try to teach in a month. I applaud Brian for doing such a great job of it. My class got the 2.0 version. I applaud him for making adjustments to the course. I would recommend this course, with the caution if you are new to statistics, it might be to your advantage to take the Duke course on Coursera first. Or read a text book.
I announced a sabbatical in my last post but I have a real problem. I love to learn. So I just started the Programming for Everybody (Python) course at Coursera. I did this because a co-worker enrolled. It is a course designed to introduce programming to non-programmers and it is really good.