I also thought that the topics covered in this course will be very relevant at my future job. A lot of the course was done in R. There was an interesting homework assignment where he gave the entire class the same data set. Whoever was able to get the lowest Mean Squared Prediction Error with their model would get a high mark. We were able to model the data however we liked. I personally used a training/test subset approach.
- Modeling a response variable as a function of several explanatory variables
- Multiple regression for a continuous response
- Logistic regression for a binary response
- Log-linear models for count data
- Finding low-dimensional structure
- Principal components analysis (PCA)
- Cluster analysis