Applied Mathematics

General targets: to acquire basic and advanced knowledge and hands-on experience on machine learning models and big data, and on optimization algorithms for the training of the models. Specific targets Knowledge and understanding: Understanding of the theoretical foundations of machine learning models and of the main optimization algorithms for their training. Applying knowledge and understanding: the student will be able to identify the machine learning model suitable for solving a given learning problem and to select the most appropriate optimization algorithm for the training of the chosen model, also taking into account practical constraints due to the applicative environment (for example, size of the problem and time limits). In addition the student will be able to correctly analyze the results provided by commercial or ad-hoc resolution software. Making judgements: ability to enucleate the most significant aspects of a learning problem and of the optimization algorithms for training the machine learning models. Communication skills: ability to enucleate the significant points of the theory, to know how to illustrate the most interesting parts with appropriate examples.