Implementing single variable Linear Regression in python
The Equation for Least Square method shall be as below-

theta(0)+theta(1).X , since you have 1 variable.

if theta(0) =0 and theta(1)=0 since you are adding it theta = np.zeros(shape=(2, 1)).

the value of Y shall be 0 hence error is 0.

To breakdown nicely you can add it like-

n = X.shape[1]
theta = np.zeros((1, n))


Now in the next run the values of theta shall change as per learning rates and in then the errors shall change too, that part you haven't reached yet, by looking at your code if I might add.

Here have a look-

https://towardsdatascience.com/linear-regression-using-python-b136c91bf0a2