Data Science & Business Informatics 1075I, 6 cfu
Informatica Umanistica 753AA, 6 cfu
Lecturer: Filippo Chiarello
FIRST LESSON: 16/09
Tuesday: 16:00-18:00 FIB M1
Friday: 16:00-18:00 FIB M1
Office hours: Wednesday from 18:00 (to be scheduled with the professor)
The course is focused on practical skills. Students will learn to apply quantitative methods for solving design problems in the context of data science and artificial intelligence. The students will acquire transversal knowledge to the Master Degree in Data Science and Business Informatics. In particular, the students at the end of the course will:
• Be aware of the whole process of value generation in a data science process
• Know available methods for designing data-driven products and services
• Be aware of the business, environmental and social impact of data science solutions
The course is in synergy with the research team B4DS, where some students interested in doing research can find placement too:
The course focus on different soft skills. Some of these skills (i.e. creativity and critical thinking) will be faced using methodological approaches, to help students develop behaviours towards the use of methods using the approach developed in the European Project Ulisse. During the activities of the course (lessons and project activities) the students will also develop the following behaviours:
• Be able to work in a diverse, multi-cultural and interdisciplinary team
• Be positive and methodological towards complex socio-technical problems
• Be curious about the continuous development of the data science sector
• Listen and discuss actively in a team
The Righ It: Why So Many Ideas Fail and How to Make Sure Yours, Alberto Savoia (2019)
The Signal and the Noise: Why So Many Predictions Fail - but Some Don't, Nate Silver (2015)
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Pedro Domingos (2015)
The grade for the exam will be computed as follows:
Non-attending students are welcome to attend the exam. All the frontal lessons will be recorded, and students will have access to the material of the course. Non-attending students are strongly encouraged to use office hours to interact with the teacher during the preparation of the exam, especially for the preparation of the project. Also, students are encouraged to work in teams even if they are not attending the course.
The percentages for non-attending students are the following:
The students will be asked to make a teamwork project, where they will design a data-science based product or service. Students will be followed in the development of the project, towards the final discussion, thanks to class activities. Attending students will also be asked to participate in the peer-to-peer evaluation of the project activities.
At the end of the project, students will have as output the following documents:
The team will send an e-mail to the professor with the Project Document and Peer Review Report at least one week before the date of the exam.
During the course, students will be asked to make a review of a scientific contribution. This can be:
At the end of the activity, students will have as output the following documents:
The student will decide the content to review and send an e-mail to the professor with the Scientific Review Document at least one week before the date of the exam.
Registration to the exam is mandatory.
The course will be blended (online and in-person) only for the frontal lessons. The hands on lessons (where students will work on the project or on exercises) will be in person only. To join a lecture online enter the virtual classroom, go to the Calendar tab and click on the scheduled lecture.