Well that's how neural networks er work. They are hand-crafted systems with a human-devised training algorithm, backprop. Their output is a model trained on data. But the algorithms that train the model, themselves, are coded manually.
Same goes for basically all machine learning algorithms. They are hand-crafted systems that train models from data.
Indeed, it is impossible to learn anything "from data".
Data is just measurement of observable variables. A prior model of the meaning of those measurements is required first to parse them into a coherent "observational model"; and then many prior models is required to parse into a representational model.
Few, if any extant "AI" systems are able to take the latter step, not least, as it requires more than measurements of the target system which are always ambiguous. (In particular, it requires a coordinated body).
Same goes for basically all machine learning algorithms. They are hand-crafted systems that train models from data.