The amount of data in industrial applications is exponentially growing. Efficient and sophisticated tools are needed to manage it. This course presents the most recent methods of data processing and content generation.
Develop the basic skills for extracting knowledge and knowledge from large data sets, in particular by forming an understanding of the value of data mining in solving real-world problems understanding of foundational concepts underlying data mining understanding of algorithms commonly used in data mining tools ability to apply data mining tools to real-world problems
At the end of the course, the student
• will have acquired knowledge of AI tools used in the business environment both to build complex predictive models and to generate new content (texts, images, sounds, videos), modeled on the needs of the recipients of the analyses
• will be able to operate at best in the business environment by exploiting a good understanding of the fundamental concepts of Predictive AI and Generative AI
• will be able to tackle a data analysis problem in a group, automatically generate a report, present it and thus understand a business phenomenon.
Coding (Matlab and/or Python and/or R), linear algebra, descriptive and inferential statistics.
In-class lectures and seminars by external experts.
“Deep learning” di Goodfellow, Bengio, Courville. MIT Press Ltd (2016)
“Generative deep learning: teaching machines to paint, write, compose, and play” di Foster. O'Reilly Media (2023)
“Applied survival analysis using R” di Moore. Springer (2016)
“Attention is all you need” di Vaswani, Shazeer, Parmar, Uszkoreit, Jones, Gomez, Kaiser, Polosukhina (2017). In Guyon, Von Luxburg, Bengio, Wallach, Fergus, Vishwanathan and Garnett (eds.). 31st Conference on Neural Information Processing Systems (NIPS). Advances in Neural Information Processing Systems. Vol. 30. Curran Associates, Inc. arXiv:1706.03762.
“Data mining: practical machine learning tools and techniques - 4th Edition” di Witten, Frank, Hall, Pal, Foulds. Kaufmann (2016)
Scientific papers and online resources for selected applications
According to official academic calendar
The exam is divided into two parts:
For students with disabilities or with DSA, please refer to the Further Information section.
Multiple choice test The test is aimed at verifying the learning of the basic concepts presented in the course.
Oral presentation of a project carried out in a group The oral presentation of the project is aimed at evaluating the ability to address a business problem, find solutions and obtain appropriate results. The evaluation takes into account the adopted methodologies, the ability to critically analyze situations and the mastery of presentation technique.
Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Sergio Di Domizio (sergio.didomizio@unige.it), the Department’s disability liaison.
