Mathematics #5: Practical Machine learning with R

I was in the US for 3 weeks on the Visa Waiver program in 2015 and stayed at a friendly AirBnB host in Berkeley nearby the UC Berkeley campus.

While I was in Berkeley I decided to check out the course offerings at the UC Berkeley Extension student program and found the class COMPSCI X460 – Practical Machine Learning (With R) interesting.

I sent an email to UC Berkeley Extension team who showed me the web site where it was written that I as a tourist is permitted to study for recreation without credits at UC Berkeley Extension. If you want to study with credits in the US, you need a student VISA known as F-1.

http://extension.berkeley.edu/static/studentservices/policies/#international

  • Your enrollment into UC Berkeley Extension course(s) must solely be for recreational purposes;
  • Your course(s) must only be incidental to your visit as a tourist to the U.S., and must not be the main purpose of your visit;
  • Your course(s) must not equal or exceed 18 instructional hours per week;
  • Your course(s) must not equal or exceed:
    1. For courses numbered X300-499: 8 semester units a term; or
    2. For courses numbered X or XB 1-299: 12 semester units per term (including concurrent enrollment courses); and,
    3. Your course(s) must not be used for credit toward a degree, diploma, certificate or other program completion award.

I attended the first introduction class at UC Berkeley Extension in the Golden Bear Center, but didn’t continue with the class since I was in the US on the Visa Waiver program for 90 days and was going to return to Norway the day after the introduction class.

The curriculum for Practical Machine learning (With R) was Max Kuhn and Kjell Johnson’s Applied Predictive Modeling, but I could not find the text book in the campus book store. The book is available on Amazon.

Extra curriculum was Hastie, Tibshirani and Friedman’s Elements of Statistical Learning.

In the first introduction class I learnt about the R programming language, how to install RStudio and the various R packages from CRAN.

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