How did they figure out the near optimal values for w and b, they are not showing this any where in this lab:
b_init = 785.1811367994083
w_init = np.array([ 0.39133535, 18.75376741, -53.36032453, -26.42131618])
Also, are there any labs that I need to solve and practice that are not solved?
Every practice lab contains some assignments you need to complete. Those are the assignments you submit for grading.
The course will teach you how to find the optimum weight and bias values.
Hi @SAM1988 , as I know, the parameters are initialized randomly, and we need to update them gradually so that the loss function gets as closer as its minimum value as possible.
Hello Sam @SAM1988, they didn’t explain that, but they could have run gradient descent behind the scene and then just put down the weights that are midway to the optimal.
Yes, every week starting from Course 1 Week 2 will have a practice lab at the end of the week. Course 1 Week 1 is a warm-up 
Cheers,
Raymond