You may restrict your experiments to a subset of the instances IF Weka cannot handle your whole dataset (this is unlikely). But remember that the more accurate your decision tree is, the better.
To the extent possible, modify the attribute names and the value names so that the resulting decision trees are easier to read.
Read Weka's ID3 and J4.8 code to determine what type of post-processing techniques they offered to increase the classification accuracy and/or to reduce the size of the decision tree. Describe that functionality in detail in your written report and experiment with this functionality. Alter Weka's code if you want to tailor it to your needs.
Your report should contain the following sections with the corresponding discussions:
Provide a detail description of the preprocessing of your data. Justify the preprocessing you apply and why the resulting data is the appropriate one for mining decision trees from it.