CODE 101801 ACADEMIC YEAR 2025/2026 CREDITS 6 cfu anno 1 COMPUTER SCIENCE 11964 (LM-18) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR INF/01 LANGUAGE English TEACHING LOCATION GENOVA SEMESTER 2° Semester OVERVIEW 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. AIMS AND CONTENT LEARNING OUTCOMES Learning how to work on a predicted analytics project, relying on machine learning, distributed computing, and data warehousing methods, algorithms, and technologies. AIMS AND LEARNING OUTCOMES 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. PREREQUISITES Basics of Machine Learning, Distributed Computing, Data Warehousing TEACHING METHODS Class and self-developed project SYLLABUS/CONTENT 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. TEACHERS AND EXAM BOARD ALESSANDRO VERRI Ricevimento: Appointment by email LESSONS LESSONS START In agreement with the calendar approved by the Degree Program Board of Computer Science. Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS ASSESSMENT METHODS 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.
