Differenze

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--- mds:d4ds:start [09/09/2021 alle 14:42 (4 anni fa)] – [Scientific Review] Filippo Chiarello
+++ mds:d4ds:start [16/09/2022 alle 11:31 (3 anni fa)] (versione attuale) – [Exam for attending students] Filippo Chiarello
@@ Linea 1: / Linea 1: @@
-====== Project Design & Management for Data Science (2021/2022) ======
+====== Project Design & Management for Data Science (2022/2023) ======
-**D4DS 2021/22**
+**D4DS 2022/23**
 ** Data Science & Business Informatics** 1075I, 6 cfu
@@ Linea 9: / Linea 9: @@
 **Lecturer**: Filippo Chiarello
-Contact: [[mailto:[email protected]|email]] - phone 050 2217318 -  [[https://www.linkedin.com/in/filippo-chiarello-2b382770/|Linkedin]]
+**Contact**: [[mailto:[email protected]|email]] - phone 050 2217318 -  [[https://www.linkedin.com/in/filippo-chiarello-2b382770/|Linkedin]]
-Office hours: **TO BE DEFINED**
+FIRST LESSON: 16/09
-==== Announcements ====
+LESSONS:
-   * **Lecture start**:\\ The first lecture will be Monday the 13th of September, 14:15‑16:00 Aula Fib C
+Tuesday: 16:00-18:00 FIB M1
-   * **Enroll on the course :!:**:\\ Each student should send an email to the professor from her/his UNIPI email account with subject **D4DS21** and the following data\\ (by doing so, the account will be included in the class mailing-list, where important announcements can be sent):
+Friday: 16:00-18:00 FIB M1
-    - **first name** and **last name** (please clarify which is which, to avoid ambiguities)
-    - **enrolment number** (numero di matricola)
+**Office hours**: Wednesday from 18:00 (to be scheduled with the professor)
-    - bachelor degree (**course of study** and **university**)
+[[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| }}
 ----
@@ Linea 26: / Linea 29: @@
 ==== 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:
+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
-•  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:
+The course is in synergy with the research team B4DS, where some students interested in doing research can find placement too:
-  * [[https://www.errequadrosrl.com/|Erre Quadro srl]]
-  * [[https://www.gatecentre.eu/aziendeingate/beam-me-up/| Beam Me Up]]
-  * [[https://www.zerynth.com/en/|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/]]
@@ Linea 50: / Linea 43: @@
 ==== 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 [[https://ulisseproject.eu/|European Project Ulisse]]. During the activities of the course (lessons and project activities) the students will also develop the following 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
@@ Linea 84: / Linea 77: @@
 The grade for the exam will be computed as follows:
-  * Project Document: 30%, evaluated by the teacher
+  * Project Document: 40%, evaluated by the teacher
-  * Project Presentation: 20%, evaluated by the teacher
+  * Project Presentation: 15%, evaluated by the teacher
   * Project Document: 10%, evaluated by peers students
-  * Peer Evaluation: 20%, evaluated by the teacher
+  * Peer Evaluation: 10%, evaluated by the teacher
-  * Report Review: 20%, 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 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.
+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:
@@ Linea 109: / Linea 102: @@
   * **Project Document**:
-*Structure: TO BE DEFINED*
   * **Project Presentation**:
-*Structure: TO BE DEFINED*
+  * **Peer Review Evaluation**
-  * **Peer Review Report**
-*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.
@@ Linea 136: / Linea 123: @@
   * **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.
@@ Linea 147: / Linea 132: @@
   * **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.//
+  * **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. //
@@ Linea 171: / Linea 156: @@
 ==== Lectures  ====
-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.
+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.
-^ N ^ Date ^ Hours ^ Title ^  Lecture Material ^ 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 | The science of questions | | Discover |
-| 3 | 20/9 | 14:15‑16:00 | Research vs Development; Products vs Services | | Define |
-| 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 | Methods for user needs analysis | | Discover |
-| 17 | 9/11 | 14:15‑16:00 | Quality function deployment for data science | | Model |
-| 18 | 15/11 | 14:15‑16:00 | Project Work: Needs and Specifications Identifications | | 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 ====
-TO BE DEFINED
-^ Date ^^ Time ^ Room ^ Info ^
-|  |  |  |  |  |