Data visualization, advanced analytics and artificial intelligence
A.A. 2024/2025
Insegnamento per
Per il calendario delle lezioni e altre informazioni consulta il sito del dottorato
Docente responsabile: Giulio Vistoli
"The aim of this course is to introduce several applications and analytical tools to investigate facts and explore data, in order to understand how these techniques are useful in various fields to obtain useful information and develop your research.
The course will consist of interventions of various types: theoretical lectures in which various aspects related to data capitalization will be addressed in an introductory way, such as data science, data monetization, the use of machine learning and AI, the use in an ethical and explainable way or to generate sustainability; practical examples of using SAS tools will then be made to explore some sample data and apply some methodologies such as supervised statistical models, neural networks, cluster analysis and classifications, various graphical tools; finally, there will be interventions by companies in the pharmaceutical or environmental fields who will talk about the use of these techniques in their context and the advantages such tools bring.
For the practical sessions, the students can have access to SAS software and to some sample data available; SAS tools are visual and user-friendly, no previous programming experience is needed, and students will be guided and supported by the lecturers, with the aim to have hands-on and experiment the usage of these technologies.
The cases that will be told and used as examples will be related to different industries and processes, and will serve to show the scope of the analytics economy and inspire in a broad way."
The course will consist of interventions of various types: theoretical lectures in which various aspects related to data capitalization will be addressed in an introductory way, such as data science, data monetization, the use of machine learning and AI, the use in an ethical and explainable way or to generate sustainability; practical examples of using SAS tools will then be made to explore some sample data and apply some methodologies such as supervised statistical models, neural networks, cluster analysis and classifications, various graphical tools; finally, there will be interventions by companies in the pharmaceutical or environmental fields who will talk about the use of these techniques in their context and the advantages such tools bring.
For the practical sessions, the students can have access to SAS software and to some sample data available; SAS tools are visual and user-friendly, no previous programming experience is needed, and students will be guided and supported by the lecturers, with the aim to have hands-on and experiment the usage of these technologies.
The cases that will be told and used as examples will be related to different industries and processes, and will serve to show the scope of the analytics economy and inspire in a broad way."
Non definiti
Modalità di valutazione
Giudizio di approvazione
Giudizio di valutazione
superato/non superato
Iscrizioni
Scadenze
Il termine di iscrizione ai corsi è previsto generalmente entro il 27° giorno del mese precedente al mese di avvio.
Come iscriversi
- Autenticarsi al servizio di iscrizione con le credenziali di Ateneo
- Selezionare l’insegnamento scelto e cliccare su Iscrizione e infine su Iscriviti
Trascurare del tutto la voce "Data di appello" che appare durante la procedura di iscrizione.
Assistenza
Per informazioni e richieste di chiarimento scrivere a: [email protected]