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====== Project Design & Management for Data Science (2022/2023) ======

**D4DS 2022/23**

** Data Science & Business Informatics** 1075I, 6 cfu

** Informatica Umanistica** 753AA, 6 cfu

**Lecturer**: Filippo Chiarello

**Contact**: [[mailto:filippo.chiarello@unipi.it|email]] - phone 050 2217318 -  [[https://www.linkedin.com/in/filippo-chiarello-2b382770/|Linkedin]]

FIRST LESSON: 16/09

LESSONS: 

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)

[[https://teams.microsoft.com/l/team/19%3aHrVduqSszKYZ4zKUwg2cC6qGyE-P_kSiRlAcOrNwdkE1%40thread.tacv2/conversations?groupId=54e2bbe6-c2f8-400f-a8e9-45d2238d02cd&tenantId=c7456b31-a220-47f5-be52-473828670aa1|LINK TO MSTeams Channel]]

{{mds:d4ds:presentazione.png| }}

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==== Objectives of the course====

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:

  * [[http://b4ds.unipi.it/]]

==== Intended Behaviours ====

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 [[https://ulisseproject.eu/|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 

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==== Books ====

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)

==== Web-Sites ====

  * [[https://www.ideou.com/pages/design-thinking-resources]]

  * [[https://ai.google/education/]]

  * [[https://nadiapiet.com/]]

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==== Exam for attending students ====

The grade for the exam will be computed as follows: 

  * Project Document: 40%, evaluated by the teacher
  * Project Presentation: 15%, evaluated by the teacher
  * Project Document: 10%, evaluated by peers students
  * Peer Evaluation: 10%, evaluated by the teacher
  * Report Review: 25%, evaluated by the teacher

==== Exam for non-attending students ====

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: 

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

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==== Project ====

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 [[https://en.wikipedia.org/wiki/Peer_assessment|peer-to-peer evaluation]] of the project activities. 

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

  * **Project Document**:

  * **Project Presentation**:

  * **Peer Review Evaluation**

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.

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==== 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**:

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. 


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=== 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 3 or 4 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 [[https://esami.unipi.it/esami/|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. //
  * **How is the oral exam organized?** //DIFFERENT GROUP MEMBERS CAN ASK TO SCHEDULE THE SECOND PART OF THE EXAM ON DIFFERENT SESSIONS.//

[[https://esami.unipi.it/esami/|Registration]] to the exam is mandatory.

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==== Lectures  ====

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.