The course encourages students to apply machine learning, distributed computing, and data warehousing methods, algorithms, and technologies in a predictive analytics project, on which students will work on their own.
Learning how to work on a predicted analytics project, relying on machine learning, distributed computing, and data warehousing methods, algorithms, and technologies.
APPLY machine learning, distributed computing, and data warehousing methods, algorithms, and technologies. methods, algorithms, and technologies on a real predictive analytics project.
Basics of Machine Learning, Distributed Computing, Data Warehousing
Class and outside preparation
Depending on the courses you passed in the first term, you are either free to work on a predictive analytcs project of your choice or you will work on a project assigned by one of the instructors.
Ricevimento: Appointment by email
ALESSANDRO VERRI (President)
GIOVANNA GUERRINI
BARBARA CATANIA (President Substitute)
In agreement with the calendar approved by the Degree Program Board of Computer Science.
Through an autonomous project, we will check the student ability to combine and apply what they learnt in the Machine Learning, Distributed Computing, and Data Wareousing courses on a concrete predictive analytics project.
