What's my target variable?
Obtaining a dataset is an important part of defining a ML problem but it's not the only one. Typically this involves the following steps:


Define the goal of the problem. Example: predict AZT level of tolerance among AIDS patients.
Obtain appropriate data for the problem.
Design the formal setting of the experiment: 


what kind of problem is it (e.g. classification)
what is the target variable and what are the features in the data
how to evaluate the quality of the results (performance measure, e.g.f1-score)
Experimental setup: ML method(s), use of cross-validation etc.