A fantastic class designed and first taught by Dr. Guy Lebanon. This class covers the principles of getting data ready for analysis and getting yourself and colleagues ready to analyze it and doing statistical based analysis of the data. You will learn how to:

  • deal with missing data,
  • gain visual insights into the data by plotting graphs,
  • created summary tables,

Then you will get an:

  • introduction to logistic regression,
  • introduction to linear regression,
  • introduction to regularization.

You will also get a thorough introduction to, and many chances to apply and improve your ability in, the R Programming Language.

You should have a working knowledge of:

  • How to code.
  • How to work with a programming language that can use vectorized code,
  • Linear algebra, like transforms, dot-product, etc.
  • Previous knowledge of the Machine Learning (ML) items like logistic and linear regression and regularization is not required, but might help.

This course is very strong on real-world usage of data prep and ML tasks. It is a great intro class to machine learning as well.

For preparations, you may want to take a look at the R lessons of the OMSCS Orientation on Udacity. You may also want to check out JHU's swirl.

Course website for Spring 2017 is here. Take note though that Spring 2017 offering of DVA had several issues, so there is no guarantee as to how future course offerings would turn out.