These are a couple of example questions, I will of course ask more and about different topics not included in this example. The questions here are intended to illustrate the kind of questions asked. Imagine these kind of questions, but about all topics covered.
 You have to compare three cars, and each car has different features. Which two cars are most similar, using Jaccard index?
 A: turbo, radio, extra suspensions, 3 year warranty
 B: radio, usb port, 3 year warranty
 C: no warranty
 If you would have used simple matching coefficient, would the result be different?
 What are the three V in big data analysis?

Classify the three cars from the first question using the following rule based classifier:
 R1: has a radio, has a turbo > buy
 R2: has no warranty, has no usb port > don’t buy
 default: > wreck

Imagine a tree building algorithm, and the data set is the one from the car example.
 List all item sets of size 2 with a support over 50%.
 What is the confidence of the following rule: {has warranty}>{usb port}?

I have the following linear equation: f(x)=0.5x+2.0
Is this the right fit for the following data set:
X Y
1 0.2
2 4.0
3 1.0