How is vector A converted to single value scalar in Andrew Ng's course?
$n_X$ is the number of feature, $400$ is the number of data.
Each of the entry of $A$ is the output of the sigmoid layer, it is between $0$ and $1$. We can then decide a threshold (typically $0.5$) such that if it is at least the threshold, we map it to $1$, otherwise, we map it to $0$.