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.
At the end of the course, students will be able to:
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 self-developed project
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.
Materials will be made available on Aulaweb.
Ricevimento: Appointment by email
ALESSANDRO VERRI (President)
According to the calendar approved by the Degree Program Board: https://corsi.unige.it/en/corsi/11964/studenti-orario
Oral exam by appointment.
Guidelines for students with certified Specific Learning Disorders, disabilities, or other special educational needs are available at https://corsi.unige.it/en/corsi/11964/studenti-disabilita-dsa
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.
For further information, please refer to the course’s AulaWeb module or contact the instructor.
