Artificial Intelligence and Data Analysis
A.Y. 2020/2021
Learning objectives
Undefined
Expected learning outcomes
Undefined
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Didactic Activity will be offered by Microsoft Teams. All classes can be followed both synchronously based (based on the second semester schedule) and asynchronously because all Lecture will be recorded and let available to students on the same platform.
In any case, the synchronous mode is preferable and strongly recommended as it allows the active participation of students through the formulation of questions and the discussion of the topics covered.
If National Regulation and University of Milan regulations, concerning social distancing, allow it, 50% of the Lessons will be held in person and simultaneously transmitted online.
Participation in face-to-face lessons will be voluntary and strongly recommended.
In any case, the synchronous mode is preferable and strongly recommended as it allows the active participation of students through the formulation of questions and the discussion of the topics covered.
If National Regulation and University of Milan regulations, concerning social distancing, allow it, 50% of the Lessons will be held in person and simultaneously transmitted online.
Participation in face-to-face lessons will be voluntary and strongly recommended.
Course syllabus
o what is Artificial Intelligence (AI)
o history of AI
o philosophy of AI
o From Human Computer Interaction to Human Computer Confluence
o Embodied Cognition and Strong/Weak AI
o Singularity and Transhumanism
o the concept of Intelligence from psychology to AI
o applied AI, with a focus on the medical/healthcare and the business fields
o AI management, present and future challenge of AI implementation
o XAI (eXplainable Artificial Intelligence)
o Ethics and AI
o AI and cognitive biases
o AI and functional areas
o Human Centered AI
o history of AI
o philosophy of AI
o From Human Computer Interaction to Human Computer Confluence
o Embodied Cognition and Strong/Weak AI
o Singularity and Transhumanism
o the concept of Intelligence from psychology to AI
o applied AI, with a focus on the medical/healthcare and the business fields
o AI management, present and future challenge of AI implementation
o XAI (eXplainable Artificial Intelligence)
o Ethics and AI
o AI and cognitive biases
o AI and functional areas
o Human Centered AI
Prerequisites for admission
No prior knowledge is required; basic informatics knowledge would be useful for the complete understanding of the main topics.
Teaching methods
The course consists in lectures supported by slides. Also other online resources will be accessed, and students will be presented with tools for computational analysis. Lessons will be streamed on Microsoft Teams and also made available for students on the course website. One time a month the lesson will be also in presence.
Teaching Resources
Il materiale didattico consiste nelle slides che verranno depositate su ARIEL e nei volumi:
Stuart J. Russell, Peter Norvig, Intelligenza artificiale. Un approccio moderno, 1998, ed. L. Carlucci Aiello, UTET Università, ISBN 9788877504067
The teaching material consists of the slides uploaded on ARIEL and in the textbooks:
Stuart J. Russell, Peter Norvig, Artificial Intelligence: A Modern Approach, 2009, Pearson Education (US), EAN: 9780136042594
Gabriella Pravettoni, Stefano Triberti
IL MEDICO 4.0 - Come cambia la relazione medico-paziente nell'era delle nuove tecnologie, EDRA (2019)
https://www.edizioniedra.it/Il_medico_40.aspx
Stuart J. Russell, Peter Norvig, Intelligenza artificiale. Un approccio moderno, 1998, ed. L. Carlucci Aiello, UTET Università, ISBN 9788877504067
The teaching material consists of the slides uploaded on ARIEL and in the textbooks:
Stuart J. Russell, Peter Norvig, Artificial Intelligence: A Modern Approach, 2009, Pearson Education (US), EAN: 9780136042594
Gabriella Pravettoni, Stefano Triberti
IL MEDICO 4.0 - Come cambia la relazione medico-paziente nell'era delle nuove tecnologie, EDRA (2019)
https://www.edizioniedra.it/Il_medico_40.aspx
Assessment methods and Criteria
Verification of the student's knowledge will be assessed through an oral test;
The candidate will be presented with questions on the entire course contents.
The candidate will be evaluated on his/her ability to respond clearly, critically and rigorously to the questions, possibly with the aid of formulas or graphs. There will be no intermediate exams. No additional materials will be needed to sustain the exam, paper and pen will be provided by the professors if needed.
The exam score is expressed in thirtieths (the exam is passed with a minimum score of 18)
The candidate will be presented with questions on the entire course contents.
The candidate will be evaluated on his/her ability to respond clearly, critically and rigorously to the questions, possibly with the aid of formulas or graphs. There will be no intermediate exams. No additional materials will be needed to sustain the exam, paper and pen will be provided by the professors if needed.
The exam score is expressed in thirtieths (the exam is passed with a minimum score of 18)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 9
Lessons: 60 hours
Professors:
Moioli Fabio, Triberti Stefano