Prove data points not enough? Estimate required number of data points?
It depends on what you mean by "needed". More training data = lower variance with the same model complexity. So when you have a small training dataset, your models will have to be very simple (like linear regression), so to have best generalization. And very simple models tend to badly represent reality.

The answer is: you need so many points, such that your validation error is below desired threshold. 30 is probably much too low for any more complex machine learning model than linear regression with one, maybe two features.