Coming up, June 2025
A worldwide top ten maths and stats summer school according to INOMICS
Organized by the Artificial Intelligence Department of the School of Computer Science of the Universidad Politécnica de Madrid.
General information
The MLAS (formerly ASDM) is an intensive set of courses providing attendees with an introduction to the theoretical foundations as well as the practical applications of some of the machine learning methods and the modern statistical analysis techniques currently in use, 12 courses of 15h each are offered during 2 weeks.
The courses are intensive and aim to introduce both the theoretical foundations and the practical applications of modern statistical analysis techniques. The students are free to choose the courses according to their interests, with the only restriction being that courses which are given in the same time block (e.g. C01 and C02; C03 and C04;…) are mutually exclusive.
A leaflet summarizing the information is available here.
Goals and prerequisites
Academic interest: This summer school complements the background of students from a variety of disciplines with the theoretical and practical fundamentals of those modern techniques employed in the analysis and modelling of large data sets.
Scientific interest: Any scientist, regardless of her field (whether engineering, life sciences, economics, etc.) is confronted with the problem of extracting conclusions from experimental data. The summer school supplies experimentalists with the sufficient resources to be able to select the appropriate analysis technique and to apply it to their specific problem.
Professional interest: The application of modern data analysis is widespread in the industry it is practically needed in nearly all disciplines. There are plenty job offers in the field: a Glassdoor.com search as of March 2017 retrieves around 9,000 offers for “data science” and around 14,000 offers for ‘data mining’, all within the USA only.
The goal of this summer school is to complement the technical background of attendees in the field of data analysis and modelling. The courses are open to any student or professional wanting to enrich her knowledge of a topic that is more and more involved in nearly all productive areas (Computer Science, Engineering, Pharmacy, Medicine, Economics, Statistics, etc.).
A second objective is to get the student acquainted with a set of computational tools for applying the learned techniques. This may involve tackling practical problems from the student’s own work environment, i.e., working with a student’s own data set.
Note that The Machine Learning and Advanced Statistics Summer School is on advanced techniques and the courses will provide insight into modern techniques that, nearly by definition, are not mathematically trivial. Although emphasis is placed on their use and not on the underlying mathematics, attendees should not be afraid or surprised of seeing some mathematics. Teachers will make the course content accessible to students from all backgrounds. To make course attendance easier, the student is supposed to be familiar with certain concepts that are described as “prerequisites” and she is encouraged to read the “before attending documents” in order to benefit from the course as much as possible.
Programme
The Machine Learning and Advanced Statistics Summer School complements the technical background of attendees in the field of data analysis and modelling.
Open to any student or professional seeking further knowledge about a field that is more and more involved in nearly all productive areas (Computer Science, Engineering, Pharmacy, Medicine, Economics, Consultancy, Sports, Statistics, etc.)
Also providing a set of computational tools to try the studied techniques on practical problems.
Teachers will make the course content accessible to students with all backgrounds.
All classes will be given in English. Each course has theoretical as well as practical hours, in which the each techniques are put into practice with software. Students should bring their own laptops with the software required for the practical sessions. Free wireless connection will be available.
- C01: Bayesian Networks Concha Bielza, Pedro Larrañaga, Bojan Mihaljević (Univ. Politécnica de Madrid)
- C02: Time Series Ana Justel, Karen Miranda (Univ. Autónoma de Madrid), Andrés Alonso (Univ. Carlos III de Madrid)
- C03: Supervised ClassificationPedro Larrañaga, Concha Bielza, Bojan Mihaljević (Univ. Politécnica de Madrid)
- C04: Statistical InferenceRomán Mínguez (Univ. de Castilla-La Mancha)
- C05: Deep LearningÁlvaro Barbero, Alberto Suárez (Univ. Autónoma de Madrid)
- C06: Bayesian InferenceConcepción Ausín (Univ. Carlos III de Madrid), Martina Zaharieva (CUNEF Universidad)
- C07: Feature Subset Selection Bojan Mihaljević, Pedro Larrañaga, Concha Bielza (Univ. Politécnica de Madrid)
- C08: ClusteringAbraham Otero (Univ. CEU San Pablo)
- C09: Gaussian Processes and Bayesian OptimizationDaniel Hernández-Lobato (Univ. Autónoma de Madrid), Eduardo Garrido (Univ. Pontificia Comillas)
- C10: Explainable Machine LearningBojan Mihaljević, Enrique Valero-Leal (Univ. Politécnica de Madrid)
- C11: Support Vector Machines and Regularized LearningÁlvaro Barbero, Carlos Alaíz (Univ. Autónoma de Madrid)
- C12: Hidden Markov Models Agustín Álvarez (Univ. Politécnica de Madrid)
Prices
The price for each one of the 12 courses is:
25% discount for AEPIA and SEIO members.
Tuition fees include attendance to lectures and educational materials.
Fees will be independent from the number of enrolments.
Registration
Courses have a maximum attendance of 40 people whereas courses with less than 6 people will not be opened (we have an average of 20 students per course, and this is very unlikely to happen). For each attended course, the student will get an assistance certificate signed by school coordinators. Course places will be filled in strict order of payment date.
Note that enrollment is only possible until Wednesday, June 10th at 18:00 (CET) for week one courses and Wednesday, June 17th at 18:00 (CET) for week two courses.
The application process is very simple. Unless otherwise stated here, all the courses have open places. To apply for one course or a set of courses, the student should make the correspondent payment and report their personal data to the organization by email (mlas@fi.upm.es). These data must comprise the following items:
- Full name, e-mail, institution and nationality
- Passport number (or national ID card number if passport is n/a)
- List of course(s) you want to enrol
- Attachment with the wire transfer proof for the total amount of fees (preferably in PDF format)
- [Optional] If you are a member of AEPIA or SEIO, then a proof of active membership. A proof of membership quota payment can do.
The bank details for the payment are as follows.
- To: MLAS
- Subject: Course(s) number(s) + your name
- Bank name: Banco Bilbao Vizcaya Argentaria BBVA
- Bank Address: Paseo de Recoletos, 10, 1. planta, E-28001, Madrid
- Account Number: 0182 2370 44 0201522862
- SWIFT: BBVAESMMXXX
- IBAN: ES74 0182 2370 44 0201522862
- Account owner: Fundación General de la Universidad Politécnica de Madrid
- Account owner address: C/ Pastor No 3, 28003, Madrid
When carrying out the payment, make sure that you cover the wiring expenses (if any), so that the amount transferred to our account matches the corresponding course fees exactly. If not, we will ask you to wire the remaining amount. Once all the information is validated, the student will receive a confirmation email.
We can prepare a proforma and/or formal invoice for the registration. We would need the student’s registration data (e.g., name, courses to enroll into, etc.) as well as institution name, VAT and address.
Cancellation and changes
It is only possible to cancel enrollment in a course for medical reasons or a rejected visa application, and only before that course begins.
If a student would like to replace one course with another, he or she must request this before Wednesday 14th for week one courses and Wednesday 21th for week two courses. We will evaluate each request and to attempt to grant it, but there might be restrictions and we cannot provide guarantees.
We are receiving questions regarding the cancellation policy in case of events related to the new Coronavirus. We expect the situation to be under control by late June. Nonetheless, cancellation is accepted and fees will be refunded in the following cases:
- The student is banned by his institution or government from attending the summer school (e.g., there is a ban on travelling to Spain)
- The UPM, Madrid or Spain government ban the celebration of summer school and similar events.
In case 1 the student would need to provide documentation confirming the ban on attending. This refund must be requested by Wednesday 17th for week one courses and Wednesday 24th for week two courses.
Logistics for attendants
Venue
The Machine Learning and Advanced Statistics Summer School takes place at UPM’s School of Computer Science, located at the Montegancedo campus, in Madrid’s Boadilla del Monte municipality, some 20 kilometers from downtown Madrid. The campus is well connected with central Madrid, via light rail line and multiple buses lines.
Course materials, practical sessions and classrooms
Course materials with be sent on the Wednesday prior to course kick-off, that is, on Wednesday 17th for week one, and Wednesday 24th for week two. On the following day, the professors will send the instructions for installing the required software. In exceptional cases this may happen earlier, if the professor considers that the amount of software to be installed is substantial.
Students need to bring their own laptops with the software required for the practical sessions of the courses. Free wireless connection will be available. We will provide data for wifi access on the first day of classes. Eduroam is available. Note that recording the classes, either in audo or in video format, is not allowed.
The courses will be held in classrooms 5101 (courses C01, C03, and C05) and 5102 (courses C02, C04, and C06), located on the first floor of Bloque 5 (see campus map).
Accomodation
The Machine Learning and Advanced Statistics Summer School does not provide lodging. The NH Ciudad de la Imagen hotel is near-by, located halfway between the campus and Madrid, reachable with a ten-minute bus ride. Two years ago students reported very poor WIFI connection in this hotel, so you should probably check this with NH before booking.
Students also stay around the Principe Pio area in downtown Madrid. It is centric and well-connected, with the commute to campus taking around 40 minutes. You can take the 573 bus at Principe Pio and it leave you right off campus.
The NH Ciudad de la Imagen might be preferable if you will follow many courses and will have little time for other activities besides attending the summer school. Lodging near Principe Pio, on the other hand, makes it easier for you to enjoy Madrid during your stay.
For a list of hotels that the UPM has agreements with, see here. You may also try contacting international.incoming@upm.es. Please cc us when emailing them.
Reaching campus
You can reach the Montegancedo campus by buses 571, 573, 591, and 865 and by light rail line ML 3. The buses are faster than the light rail and leave you at campus or very close to it, while the light rail station is about one kilometer from campus.
From NH Ciudad de la Imagen Hotel
You can catch buses 571 and 573 in front of the hotel and the light-rail at the José Osbert ML 3 station.
From Madrid
- Colonia Jardin (metro line 10). You can catch the buses 571, 573 and 591 here. You can catch the light rail at the ML3 Colonia Jardin station.
- Ciudad Universitaria (metro line 6). Catch the 865 here.
- Aluche (metro line 5). Catch the 591 here or the 571 here.
- Principe Pío (metro lines 6 and 10). Catch the 573 here.
Getting off at the campus
Buses 591 and 865 leave you on campus. With 591 you get off at the last station whereas with 865 it’s at next-to-last, called ‘Facultad de Informática’.
If arriving with 571 or 573 you need to get off at the ‘Facultad de Informática’ bus station (station name is shown on a display inside the bus, on the front side), and walk to entrance.
If arriving by light-rail you will have to walk 1.4 kilometers to campus. As you leave the light-rail station, turn right and walk down Avda. Montepríncipe.
Click here for a detailed map of campus and surroundings.
Buses timetable
Here are the timetables for the 571, 573, 591 and 865 buses in direction from Madrid to campus. In direction campus to Madrid, the timetables are these: 571, 573, 591 and 865. Please note that for 571 and 573 the timetables differ in June and July; look for ‘Vigente Julio’ in the upper right corner of a box for July and ‘Vigente de 1 de septiembre a 30 de junio’ for June.
Tickets
A single trip for 591, 865 and the light rail costs 2 euros whereas a 10-rides ticket costs 12.20 euros. A single ride with 571 and 573 costs 2.60 euros whereas a 10-rides tickets costs 16.10 euros. See https://www.redtransporte.com/madrid/precios-abonos.html (In Spanish).
Further information
Madrid underground: https://www.metromadrid.es/en
Madrid transport: https://www.crtm.es/
Eating at campus
The cafeteria is located in Bloque 3 (see campus map). It opens from 8:00 to 20:00 and serves sandwiches, salads, drinks, hamburgers, and other dishes.
Lunch is served from 13:00 to 16:00. The self-service menu includes a starter, a main dish, a dessert and bread for 6.60€ with a drink (menu con bebida) and 6.10€ without a drink (menu sin bebida). You can also buy a 10-meal ticket (menu 10 comidas) for 53€. You for the meal at directly at the cash register.
There are microwave ovens that you can use if you want to bring you own food.
Services at the campus
Some of the services provided on campus, such as study rooms, are listed here. The library and study rooms and areas are located in Bloque 1.
The preferred entrance to the building is via Bloque 5.
Contact
School coordinators: Bojan Mihaljević and Laura Gonzalez Veiga Tel.: +34 91 067 3093 mlas@fi.upm.es School directors: Pedro Larrañaga Tel.: +34 91 067 2896 Concha Bielza Tel.: +34 91 067 2883 | Escuela Técnica Superior de Ingenieros Informáticos Univ. Politécnica de Madrid Campus Montegancedo s/n 28660 Boadilla del Monte, Madrid Spain |
Previous editions photographs
ASDM(Now MLAS) 2024
First Week
Second Week
ASDM(Now MLAS) 2023
First Week
Second Week
ASDM(Now MLAS) 2019
First Week
Second Week
ASDM(Now MLAS) 2018
First Week
Second Week
ASDM(Now MLAS) 2017
First Week
Second Week
ASDM(Now MLAS) 2016
First Week
Second Week
ASDM(Now MLAS) 2015
First Week
Second Week
ASDM(Now MLAS) 2014
First Week
Second Week
ASDM(Now MLAS) 2013
First Week
Second Week
ASDM(Now MLAS) 2012
First Week
Second Week