how to modify a 2D numpy array at specific locations without a loop?

Adding to what others have said, you can modify these elements using fancy indexing as follows:

In [39]: rows = [0,1]

In [40]: cols = [2,2]

In [41]: a = np.arange(1,10).reshape((3,3))

In [42]: a[rows,cols] = 0

In [43]: a
Out[43]: 
array([[1, 2, 0],
       [4, 5, 0],
       [7, 8, 9]])

You might want to read the documentation on indexing multidimensional arrays:
http://docs.scipy.org/doc/numpy/user/basics.indexing.html#indexing-multi-dimensional-arrays

The key point is:

if the index arrays have a matching shape, and there is an index array
for each dimension of the array being indexed, the resultant array has
the same shape as the index arrays, and the values correspond to the
index set for each position in the index arrays.

Importantly this also allows you to do things like:

In [60]: a[rows,cols] = np.array([33,77])

In [61]: a
Out[61]: 
array([[ 1,  2, 33],
       [ 4,  5, 77],
       [ 7,  8,  9]])

where you can set each element independently using another array, list or tuple of the same size.