Read part of "an introduction to R" (available from R homepage) and realize different types of objects (e.g., vector, factor, list, data frame etc.).
Find any package which can construct decision trees. You can use this package to classify the data set "iris." This set is available from R by default, so you can use
> data(iris)to get it. You then randomly separate the iris data to 3/4 for training and 1/4 for testing.
Use the package to do training and testing, and write a report (<= 2 pages in English) showing your procedure and results (i.e., testing accuracy).
At this stage we do not know yet how the tree is constructed.