Partners
MLCC is part of the ELLIS Genoa activities and is made possible by the contributions of the DIBRIS and DIMA Departments of UniGe.
At a glance
The Machine Learning Crash Course (MLCC) provides an introduction to the fundamental concepts and algorithms of Machine Learning. The course is suitable for undergraduate/graduate students, as well as professionals. It is open to students from any University upon selection.
Attendance will be exclusively in person, and the course will not be streamed online.
Machine Learning is key to develop intelligent systems and analyze data in science and engineering. Machine Learning systems enable intelligent technologies such as Siri, Google self-driving car, or Chat-GPT to name a few. At the same time, Machine Learning methods help deciphering the information in our DNA and make sense of the flood of information gathered on the web, forming the basis of a new “Science of Data”. This course introduces the fundamental methods at the core of modern Machine Learning. It covers theoretical foundations as well as essential algorithms.
The university credits granted for attendance of the course and/or successful completion of the test are established by the Director of your specific course of study, depending on your university/course criteria.
For those who want to take the final test, it will consist in completing remotely the notebooks that the class will work on during the labs, and writing a report commenting on the numerical results obtained. Active attendance will be part of the evaluation.The course is self contained but assumes basic knowledge in calculus and probability and programming.
Logistics
The school will be held in our beautiful Genova, in the DIBRIS/DIMA building in Via Dodecaneso 35, 16146, home of MaLGa Center.
The course will be held in the DIBRIS Department building of Via Dodecaneso 35, Genova. Indications to the classroom will be visible at the entrance. You will have access to vending machines during the breaks betweein classes. We suggest bringing your own laptop, but please keep into consideration that, due to the number of expected participants, your battery should be fully charged.
We will have a 1.5-hour lunch break every day: although there is a bar close to the department, you are encouraged to bring your own lunch and enjoy the break with your peers. There are common areas just out of the classroom where you will be able to sit and have lunch.
Speakers
Classes will be held by MaLGa Center faculty members from UniGe’s DIBRIS and DIMA Departments.
Programme
Classes on theoretical and algorithmic aspects will be complemented by practical lab sessions.
Monday, June 15, 2026
Welcome
9:15-9:30 - Welcome & Opening
Class
9:30-11:00 - Class 1 - Introduction to Statistical Machine Learning
Lorenzo Rosasco
Class
11:30-13:00 - Class 2 - Training and Testing: the Holdout-Method
Lorenzo Rosasco
Lab
14:30-16:30 - Lab 1
Leisure activity
16:30-17:30 - Aperitif
Tuesday, June 16, 2026
Class
9:30-11:00 - Class 3 - Empirical Risk Minimization with Linear Models
Nicoletta Noceti
Class
11:30-13:00 - Class 4 - Optimization and SGD
Cesare Molinari
Lab
14:30-16:30 - Lab 2
Wednesday, June 17, 2026
Workshop
Workshop TBA
Thursday, June 18, 2026
Class
9:30-11:00 - Class 5 - Kernel Methods
Nicoletta Noceti
Class
11:30-13:00 - Class 6 - Neural Networks
Nicoletta Noceti
Lab
14:30-16:30 - Lab 3
Friday, June 19, 2026
Class
9:30-11:00 - Class 7 - Sparsity and variable selection
Cesare Molinari
Class
11:30-12:45 - Class 8 - Dimensionality Reduction and PCA
Cesare Molinari
Goodbye
12:45-13:00 - Goodbye
How to apply
Applications are open until midnight on the 1st of March; notifications of acceptance will be sent by the 1st of April.
Submit application
Deadline on Sunday, March 1, 2026
Acceptance notification Wednesday, April 1, 2026
Registration Fees
Upon acceptance of your application, you will be requested to pay a registration fee, depending on your role and affiliation.
| role | fee |
|---|---|
| UniGe and IIT affiliates | waived |
| Non-UniGe students and postdocs | €50 |
| Non-UniGe professors | €100 |
| Professionals | €300 |
Organization
Only for information which is not available online, please refer to MaLGa’s Lab Manager.