MLCC 2017
Machine Learning Crash Course

Course at a Glance

The course will be held on the last week of June (26th-30th) at DIBRIS (University of Genoa, Italy)

Machine Learning is a key to develop intelligent systems and analyze data in science and engineering. Machine Learning engines enable intelligent technologies such as Siri, Kinect or Google self driving car, 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 provides an introduction to the fundamental methods at the core of modern Machine Learning. It covers theoretical foundations as well as essential algorithms. Classes on theoretical and algorithmic aspects are complemented by practical lab sessions.

This introductory course is suitable for undergraduate/graduate students, as well as professionals.

Course Structure:

  • 26/06 Monday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
  • 27/06 Tuesday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
  • 28/06 Wednsday 9:30-12:30 Talks
  • 29/06 Thursday 9:30-13:00 Lessons - 14:00-16:00 Laboratory
  • 30/06 Friday 9:30-13:00 Lessons

The course started in 2013 has seen an increasing national and international attendance over the years with a peak of over 100 participants in 2015.

NOTE: the course has no registration fee, but participants need to take care of their travel and accommodation needs -- see below for a list of hotels.

Notification of acceptance: To be announced.

Related courses:

Basic Info


Classes will take place at the Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) of the University of Genova in Via Dodecaneso 35, 16146 Genova. See here for directions and travelling information

(new!) Morning classes (theory) will be held in classroom 506. Laboratories will take place in rooms SW1,SW2 and 218. Directions to the classrooms will be provided at the DIBRIS entrance in Via Dodecaneso 35.


Genova is in the region of Liguria in the Italian Riviera (see here or here for some nice pics and a video).


Here you can find a list of hotels near the department (~ 20' walk) or in the city centre (~20' by bus).


Here is a list of places where you can go for lunch. And here is a link to the online map.

Extra Infos

For more info write to:
anselmi [at] mit [dot] edu
gianmaria.marconi [at] iit [dot] it


Lorenzo Rosasco

Universita' di Genova
(also Istituto Italiano di Tecnologia and Massachusetts Institute of Technology)

lorenzo (dot) rosasco (at) unige (dot) it


126/069:30 - 11:00Introduction to Machine LearningLect_1
226/0611:30 - 13:00Local Methods and Model SelectionLect_2
326/0614:00 - 16:00Laboratory 1: Local Methods for Classification Lab 1
427/069:30 - 11:00Regularization Networks I: Linear ModelsLect_3
527/0611:30 - 13:00Regularization Networks II: KernelsLect_4
627/0614:00 - 16:00Laboratory 2: Regularization NetworksLab 2
Talk28/069:30 - 10:10Pietro Leo, Executive Architect & CTO, IBM Italy Slides
Talk28/0610:10 - 10:35Enrico Ferrari, R&D Manager, Rulex Inc. Slides
28/0611:00 - 11:30Coffee Break
Talk28/0611:30 - 12:10Giovanni Zappella, Machine Learning Scientist, Amazon Developement Center Germany
Talk28/0612:10 - 12:35Luca Nardelli, Founder and CTO @ Erya, Horus Technology
729/069:30 - 11:00Dimensionality Reduction and PCALect_5
829/0611:30 - 13:00Variable Selection and SparsityLect_6
929/0614:00 - 16:00Laboratory 3: PCA and SparsityLab 3
1030/069:30 - 11:00ClusteringLect_7
1130/0611:30 - 13:00Data Representation: Deep LearningLect_8

Applications are currently closed


Fabio Anselmi

Massachussets Institute of Technology (MIT)
Istituto Italiano di Tecnologia (IIT)
Laboratory for Computational and Statistical Learning (LCSL)

anselmi [at] mit [dot] edu

Raffaello Camoriano

Istituto Italiano di Tecnologia (IIT) - iCub Facility
Laboratory for Computational and Statistical Learning (LCSL)

raffaello.camoriano [at] iit [dot] it

Gian Maria Marconi

Istituto Italiano di Tecnologia (IIT) - iCub Facility
Laboratory for Computational and Statistical Learning (LCSL)

gianmaria.marconi [at] iit [dot] it