Laboratory of data modelling

A.Y. 2020/2021
Overall hours
FIS/05 FIS/06
Learning objectives
The course will provide the student with tools to interpret physical data in a statistically correct way with suitable models, also with the help of hands-on exercises, The course combines aspects of data science with physical modelling.
Expected learning outcomes
The student will be able to build quantitative models starting form a set of physics (or other) data, to estimate their reliability and to build null models.
Course syllabus and organization

Single session

Lesson period
Second semester
The teaching will be delivered entirely remotely in the event of mobility limitations related to the health emergency. In this case the lessons will be held in virtual classrooms (zoom platform) in synchronous connection, with the possibility of real-time interaction between students and the teacher. The teaching material used for the delivery of the lessons will be made available to students.
Course syllabus
The course program will be based on a series of experiments based on a rigorous statistical model of physical problem. Each experiment will be self-contained and will last approximately 9-12 lab hours, during which the students will need to interact the the data (generally taken from large scientific datasets), formulate the physical interpretation, model the process of measurements in a statistical sound way, and write a program to perform the analysis. Each experiment will cover a different physical field.
Prerequisites for admission
The contents of the three-year degree physics and mathematics courses are considered indispensable. In addition, the contents of the course "Probabilità e statistica" will be frequently used. The laboratory experiments will be carried out using the Python 3 programming language.
Teaching methods
The course includes a series of lectures in which the necessary concepts are provided. Additionally, programming techniques in the Python language are also briefly introduced. Then, at the beginning of each experience, the physical problem that is intended to be solved is briefly described: this way the students are able to carry out the analysis independently.
Teaching Resources
David MacKay, "Information Theory, Inference, and Learning Algorithms", Cambridge University Press, 2003
Assessment methods and Criteria
During the lab hours, the students, divided into groups, will have to carry out the assigned task independently. The results obtained must then be presented by each group in a short report, which will be evaluated. The final evaluation will take into account the marks obtained by each student in the reports and the result of an oral exam (lasting approximately 45 minutes).
FIS/05 - ASTRONOMY AND ASTROPHYSICS - University credits: 0
Laboratories: 48 hours
Lessons: 14 hours