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Project Design & Management for Data Science (2021/2022)

D4DS 2021/22

Data Science & Business Informatics 1075I, 6 cfu

Informatica Umanistica 753AA, 6 cfu

Lecturer: Filippo Chiarello

Contact: email - phone 050 2217318 - Linkedin

Office hours: TO BE DEFINED

Link to the MSTeams –> LINK

Objectives of the course

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:

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:

Intended Behaviours

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)


Exam for attending students

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

Exam for non-attending students

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


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:

  • Project Document:

*Structure: TO BE DEFINED*

  • Project Presentation:

*Structure: TO BE DEFINED*

  • Peer Review Evaluation

*Structure: TO BE DEFINED*

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.

Scientific Review

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

At the end of the activity, students will have as output the following documents:

  • Scientific Review Document:

*Structure: TO BE DEFINED*

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.

Project FAQ

  • What do I need to start the project? You need a team and a *users' 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 happens if we miss the deadline? You will have to wait for the next exam session.
  • What happens 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 document 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.
  • What if the project document is not sufficient?A negative evaluation of the project document may require to rework some parts, submit a revised document and schedule a new exam (possibly at the next exam session). In this case, the teacher will communicate the decision to the students before the date of the exam. If no communication after the project document presentation is received, it means that the project has received a positive evaluation. A positive evaluation of the project allows each group member to access the oral part of the exam.

Exam FAQ

  • 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 is organised around the project and the report. After the team presentation of the project, we will have a discussion starting from the project, the report and (eventually) some of the topics covered by the course.
  • 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.

Registration to the exam is mandatory.


The course will be blended (online and in-person). To join a lecture online enter the virtual classroom, go to the Calendar tab and click on the scheduled lecture. The link to MSteams channel will appear soon.

Monday class —→ Aula Fib C Tuesday class —→ Aula Fib L1

MSTeams channel —→ LINK

N Date Hours Title Module
1 13/9 14:15‑16:00 Introduction to the course and overview of the design process Design
2 14/9 14:15‑16:00 Overview of the design process Design
3 20/9 14:15‑16:00 Methods for user needs analysis Discover
4 21/9 14:15‑16:00 Project Kick-Off: rules, groups definition and preliminary brainstorming Design
5 27/9 14:15‑16:00 Conflict Management Collaborate
6 28/9 14:15‑16:00 Creativity Discover
7 4/10 14:15‑16:00 Critical Thinking Discover
8 5/10 14:15‑16:00 Scope Definition Define
9 11/10 14:15‑16:00 Objective and OKR Define
10 12/10 14:15‑16:00 Project Work: Definition of scope and objectives Define
11 18/10 14:15‑16:00 Project Management for Data Science: Introduction Controll
12 19/10 14:15‑16:00 Project Management for Data Science: Methods Controll
13 25/10 14:15‑16:00 Project Management for Data Science: Laboratory Controll
14 26/10 14:15‑16:00 Project Work: Plan Preparation Controll
15 2/11 14:15‑16:00 Educathons: how to teach and evaluate design skills for data science Collaborate
16 8/11 14:15‑16:00 AI meet Design Model
17 9/11 14:15‑16:00 Quality function deployment for data science Model
18 15/11 14:15‑16:00 Project Work: Specifications Model
19 16/11 14:15‑16:00 Query Design Model
20 22/11 14:15‑16:00 Scientific Literature Analysis Map
21 23/11 14:15‑16:00 Technological Mapping Map
22 29/11 14:15‑16:00 Dara driven technical and economical feasibility Map
23 30/11 14:15‑16:00 Project Work: Spec definition Map
24 6/12 14:15‑16:00 Pre-Totyping 1 Make
25 7/12 14:15‑16:00 Pre-Totyping 2 Make
26 13/12 14:15‑16:00 Project Work: Revise Design
27 14/12 14:15‑16:00 Writing Reports Comunicate
28 20/12 14:15‑16:00 Presentation Design Comunicate
29 21/12 14:15‑16:00 Project Work: Presentations Design Comunicate

Exam sessions


Date Time Room Info
mds/d4ds/start.1631527859.txt.gz · Ultima modifica: 13/09/2021 alle 10:10 (21 mesi fa) da Filippo Chiarello