Questa è una vecchia versione del documento!
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
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:
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)
The grade for the exam will be computed as follows:
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:
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:
*Structure: TO BE DEFINED*
*Structure: TO BE DEFINED*
*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.
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:
*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.
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 |
TO BE DEFINED
Date | Time | Room | Info | |
---|---|---|---|---|