I just felt that it might be worthwhile to note that pandas also has this functionality. Depending on what case you are dealing with exactly, pandas might be a worthy tool to invest time in.
import pandas as pd
times = pd.date_range('2012-10-01', periods=289, freq='5min')
This returns a pandas timeseries-index. Which can be converted to numpy arrays.
np.array(times)