Lecturer: Filippo Chiarello

Contact: email - phone 050 2217318

Office hours: TO BE DEFINED

The course is focused on practical skills. Students will learn to apply quantitative methods for solving design and management problems in the context of data science and artificial intelligence. The students will acquire knowledge that is transversal 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

• Understand the differences between research projects and a development process

• Be aware of the business, environmental and social impact of data science solutions

The course has been co-designed with three companies of the innovation ecosystem of Pisa:

• Erre Quadro srl
• Beam Me Up
• Zerynth

These companies have helped to select the content for the course and are open have students for traineeships and work collaborations.

The course is also in synergy with the research team B4DS, where some students interested in doing research can find placement too:

• http://b4ds.unipi.it/

The course has a fo us 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)

• https://www.ideou.com/pages/design-thinking-resources

• https://ai.google/education/

• https://nadiapiet.com/

The grade for the exam will be computed as follows:

Project Document: 30%, evaluated by the teacher Project Presentation: 20%, evaluated by the teacher Project Document: 10%, evaluated by peers students Peer Evaluation: 20%, evaluated by the teacher Report Review: 20%, evaluated by the teacher

Registration to the exam is mandatory.

Non-attending students are welcome to attend the exam. All the 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:

Project Document: 30%, evaluated by the teacher Project Presentation: 20%, evaluated by the teacher Paper Review: 50%, evaluated by the teacher

Registration to the exam is mandatory.

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.

During the course, students will be asked to make a review of a scientific contribution, This can be:

• A scientific paper
• A book
• An article on a blog or medium
• A video on youtube
• Others

The student will decide the content to review and send an e-mail to the professor at least one week before the date of the exam. The report will be in the form of a short report (two pages).

Here is a list of already discussed contents (can not be taken again):

• What do I need to start the project? You need a team and a need. The need has to be discussed with the teacher, during a lecture or during office time.
• How many people can work together on the same project? Projects are assigned to groups of two or three people. Exceptionally, single students can be allowed (especially non-attending students), but a solid motivation is needed.
• When is the deadline for submitting the project? The project document and presentation need to be sent to the teacher at least one week before the exam date.
• What does it happen if we miss the deadline? You will have to wait for the next exam session.
• What does it happen if a person leaves the group? You must notify immediately the teacher and choose if you prefer to complete the work individually or change the composition of the team
• How do we deliver the project? You must send the teacher a project report in .pdf following the. decided structure and page limits. Optionally, you can submit annexes.
• When do we discuss the project? Preferably, at the first exam session that follows the delivery of the project.
• Is it necessary to have already delivered the project in order to register for the exam? No it is not. But of course, the project must be delivered in time for being presented and discussed at the actual oral exam.

• How do we register for the exam? As usual, you must enter your choice on the ESAMI portal.
• What are the dates of the exam? THE DATES ADVERTISED IN THE ESAMI PORTAL ARE NOT NECESSARILY THOSE OF THE ACTUAL EXAM. After you register for the exam, on the basis of the projects received and any other constraint communicated by each student, the teacher will post a tentative schedule on this web page and will inform you by email or on Teams.
• How is the exam organized? The exam is oral and it is organised in two parts: the first part will focus on the project discussion, the second part will involve all topics covered by the course. Due to the current pandemic situation, all exams will take place remotely, via the Microsoft Teams platform.
• How is the project discussion organized? ALL GROUP MEMBERS MUST BE PRESENT TO THE PROJECT DISCUSSION. All group members must demonstrate they have participated to all the activites of the project. A negative evaluation of the project may require to rework some parts, submit a revised report and schedule a new exam (possibly at the next exam session). A positive evaluation of the project allows each group member to access the second part of the exam.
• How is the second part of the exam organized? DIFFERENT GROUP MEMBERS CAN ASK TO SCHEDULE THE SECOND PART OF THE EXAM ON DIFFERENT DAYS. Questions may involve (but are not limited to): most relevant concepts, definitions, terminology and techniques; their intuitive meaning and formalization; proof sketches of formal statements; small-sized exercises. Arguments marked as optional in the lectures table below can be discussed upon student request.
• Is it possible to pass the first part of the exam and fail the second? Let's hope it won't happen, but yes, it is possible, in which case the student will need to register for one of the next exam sessions. Depending on each single case, a new project may also be assigned.

• lecture rescheduled:
  The lecture of thursday Oct. 15 has been rescheduled on wednesday Oct. 28, 16:15-18:00

• lecture canceled:
  The lecture of thursday Oct. 15 is canceled due to personal matters and will be rescheduled (possibly on a wednesday)

• lecture canceled:
  The lecture of monday Sept. 21 is canceled due to election day

• covid-19:
  Due to the covid-19 alert, all lectures are held online on the Microsoft Teams platform. Click to enter the virtual classroom

• as the course starts:
  Each student should send an email to the professor from his/her favourite email account with subject MPB20 and the following data
  (by doing so, the account will be included in the class mailing-list, where important announcements can be sent):
  1. first name and last name (please clarify which is which, to avoid ambiguities)
  2. enrolment number (numero di matricola)
  3. bachelor degree (course of study and university)

Virtual classroom: To join a lecture enter the virtual classroom, go to the Calendar tab and click on the scheduled lecture.

Virtual classroom: To join a lecture enter the virtual classroom, go to the Calendar tab and click on the scheduled lecture.

• A.A. 2019/20
• A.A. 2018/19
• A.A. 2017/18
• A.A. 2016/17
• A.A. 2015/16
• A.A. 2014/15
• A.A. 2013/14