"Data scientists is the sexiest job of the 21st century". This sentence is still valid after 10 years considering the increasingly pervasive role of data in the world of research, industry but also everyday life. Due to the growing demand of data scientists, universities face new challenges, related to the ability to offer specific training courses and which must also take into account the need for upskilling and reskilling of students with different backgrounds. The teaching of data science is still very young compared to other fields that have well-structured and defined educational paths, skills, and knowledge shared with the scientific community and with the market. It is generally accepted that the data scientist must have solid skills in computer science and statistics, but other skills relating to, for example, legal and ethical aspects are relevant. Moreover, the data scientist must have skills and knowledge related to the use of the so-called "soft skills" such as communication, the use of data visualization. However, there is still no clear and shared minimum set of specific skills in the abovementioned areas that all data scientists must possess. The initial skills that a student must have in order to access a data science path are not yet shared. In the last two years, due to the covid pandemic, all teaching and laboratory activities were provided in a pure online form. For traditional face-to-face teaching methods, there is a need to evaluate and experiment, on a large scale, with new teaching methods that take advantage of the opportunities offered by online teaching without losing the opportunity of face-to-face lectures and labs. Finally, there is no shared understanding of how much a data scientist must know about the application domain in which s/he is working and how this knowledge can be taught in a university course.

The first data science education workshop wants to bring experts and professors that have formal roles in the management of training activities discussing various issues arising in the design, deploy and manage training courses for data science.

Interesting topics include, but are not limited to:

• lesson learned from existing master/bachelor degrees;
• new educational challenge in the field of data science
• the role of multidisciplinary for data science
• proposal of new teaching tools devoted to data scientists
• the role of other areas different from computer science and statistics in the curriculum of a data scientist
• how to close the gender gap in data science education
• how to learn ethical and legal issues related to data science

Important Dates
Abstract Submission deadline: August 25, 2022
Notification of acceptance: August 30, 2022
Conference days: September 20-21, 2022
Workshop Day: September 20, 2022 (14.00 to 18.00)

To participate in the workshop, you must register here and you must send an abstract of up to 1 page to:

• Andrea Maurino (University of Milano Bicocca), andrea.maurino@unimib.it
• Silvia Salini (University of Milano), silvia.salini@unimi.it

Accepted abstracts will be presented orally at ITADATA 2022; each will be allocated a 15-minute slot for oral presentation.