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Home   >  Master's & postgraduate courses  >  Education  >  Summer Course in Monte Carlo and Bayesian Filtering
We advise you! Request information or admission
  • discount

    €300 discount for FME-UPC students

  • discount

    €250 discount for students from other UPC or UB schools, adjunct faculty from UPC or UB, and full-time faculty from UB not affiliated with the MESIO program

  • discount

    €200 discount for students from other universities

  • discount

    Free for full-time faculty at the UPC and MESIO UB or involved departments

Presentation

Edition
1st
Hours
15
Delivery method
Face-to-face
These courses will be conducted 'face-to-face' and will also be streamed live.


Language of instruction
English
Fee
€400
Notes payment of enrolment fee and 0,7% campaign
Registration open until the beginning of the programme or until end of vacancies.
Start date
Start date: 07/07/2025
End date: 11/07/2025
Timetable
Monday: 9:00 am to 12:00 pm
Tuesday: 9:00 am to 12:00 pm
Wednesday: 9:00 am to 12:00 pm
Thursday: 9:00 am to 12:00 pm
Friday: 9:00 am to 12:00 pm
Taught at
Facultat de Matem脿tiques i Estad铆stica (FME)
C/ Pau Gargallo, 14. Edifici U.
Barcelona
Why this programme?
This course is part of the XVIII Summer School of the Master's degree in Statistics and Operations Research (MESIO UPC-UB).

Dynamic systems
lie at the heart of numerous scientific and industrial processes, from object tracking in engineering to forecasting economic or environmental variables. Modeling and analyzing them requires a powerful combination of statistical and computational techniques. This course offers an intensive and hands-on introduction to Bayesian filtering and Monte Carlo methods, essential tools for tackling these problems from a modern probabilistic perspective.

The Monte Carlo and Bayesian Filtering course bridges classical methods, such as the Kalman filter, with cutting-edge simulation-based approaches like particle filtering (Sequential Monte Carlo). It provides a unique opportunity to build a solid foundation in both the theory and practice of these techniques, through applied examples and computational exercises in a collaborative and stimulating environment.

Primarily intended for students of the MESIO master’s program. The seminars can be recognized with 3 ECTS if 2 courses are completed and passed, and with 5 ECTS if 3 courses are completed and passed, subject to approval by the Faculty of Mathematics.
Aims
  • Understand the principles of Bayesian inference and its application to dynamical systems.
  • Learn the structure and inference strategies in state-space models.
  • Develop working knowledge of the Kalman filter and its nonlinear extensions.
  • Master Monte Carlo techniques, especially importance sampling and sequential Monte Carlo (particle filters).
  • Apply these methods to real-world(-like) problems through guided exercises and coding projects.
Who is it for?
Mostly PhD students. MSc student with good mathematical level (and enough maturity) may also follow it. Other researchers are more than welcome!

Students should have a basic background in linear algebra, probability, and calculus. Prior exposure to Bayesian statistics or time series is helpful but not required. Familiarity with a programming language such as MATLAB, Python, or R is expected for the hands-on exercises.

Software Requirements
Proficiency in at least Python, R, or MATLAB.
Students must bring their own laptops.

Training Content

List of subjects
15h
Monte Carlo and Bayesian filtering
  • Introduction to statistical learning
  • Bayesian inference: from analytical models to intractable integrals
  • Monte Carlo methods: basic ideas, importance sampling, rejection sampling, MCMC
  • State-space models and Bayesian filtering
  • The Kalman filter and extensions (e.g., RTS smoother, nonlinear filters)
  • Sequential Monte Carlo: particle filtering foundations and advanced methods
  • Hands-on projects implementing algorithms
Degree
Certificate issued by the Fundaci贸 Polit猫cnica de Catalunya.

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.

The course combines theoretical lectures with interactive problem-solving and programming labs. Each topic includes a mini-project where students implement and apply the discussed algorithms. Participants are expected to engage in daily exercises and present their results on the final day. Emphasis is placed on both conceptual understanding and practical coding skills. The proposed split is 2h of lectures + 1h of coding per day.
Virtual campus
The students on this summer course will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the programme's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Academic management
  • Langohr, Klaus
    info
    /
    PhD in Statistics from the Polytechnic University of Catalonia (UPC). Graduate in Statistical Sciences and Techniques from the University of Dortmund (Germany). Associate professor at the Department of Statistics and Operations Research of the UPC.
Teaching staff
  • Elvira Arregui, Victor
    info

    Victor Elvira is a Professor with a Personal Chair in Statistics and Data Science at the School of Mathematics at the University of Edinburgh since 2023. Previously, he was a Reader (2019-2023) and the Director of the Centre for Statistics (2022) also at the University of Edinburgh (UK). From 2016 to 2019, he was an Associate Professor at the engineering school IMT Lille Douai (France). From 2013 to 2016, he was an Assistant Professor at University Carlos III of Madrid (Spain).

Request information or admission

Information and guidance:
Isabel de la Fuente Larriba
(34) 93 115 57 51
Request received!
After we have registered your request, you will receive confirmation by email and we will be in touch.

Thank you for your interest in our training programmes.
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Name:

Programme: Monte Carlo and Bayesian Filtering

Fee: €400

Submit and make the payment
  • If you have any doubts.
  • If you want to start the registration procedure.
How to start admission
To familiarise yourself with the registration process for this programme, please contact:

Isabel de la Fuente Larriba
(34) 93 115 57 51
isabel.delafuente@talent.upc.edu




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ACADEMIC AND ECONOMIC REGULATIONS

The Fundaci贸 Polit猫cnica de Catalunya reserves the right to modify content, price, location, timetable and dates prior to the start of the course. Registration on the course will not be confirmed until payment has been made.

Registration rights. The interested party must make payment of the specified registration fee for the course. This fee will be deducted from the full course fee and will only be reimbursed if the applicant is not admitted.

Cancellation or deferment.The Fundaci贸 Polit猫cnica de Catalunya reserves the right to cancel or defer a course if the minimum number of students is not met. In case of cancellation or non-admittance, the Fundaci贸 Polit猫cnica de Catalunya will return all amounts paid in full, without any additional compensation. In case of deferment, applicants may request reimbursement of fees paid.

Cancellation of registration.
In the event of withdrawal or cancellation of the registration, the student must notify the UPC School in writing beforehand.
  • If this request for cancellation is made 45 days before the start of the programme, the UPC School will retain only 30% of the total registration fee and refund the difference paid.
  • In the event that the application request is made within 45 calendar days and the beginning of the programme, the UPC School will retain 60% of the registration fee.
  • No applications for refunds may be made after the programme has started.
Under exceptional circumstances, refunds of the registration fee will be made if the student's cancellation is due to one of the following circumstances:
  • Denial of a visa, subject to submission of supporting documentation. In this case, the UPC School will refund the registration fee less 300 Euros for administrative expenses.
  • Serious illness or accident accredited by an official medical certificate, stating the start date of the illness and the anticipated convalescence period. In this situation the UPC School's decision will be as follows:
    • If the notification takes place up to one month after the start of the programme, it will refund the amount actually paid, less 300 Euros as administrative expenses.
    • No refunds will be made after a month after the start of the programme. It will be only be possible to use the amount paid as a deposit for the registration fee of the next programme. This procedure entails no administrative fee for the student. The price difference between the new registration fee and the amount previously paid will be payable by the student under all circumstances.

Changes in registration. Any changes in registration, previously authorised by the Fundaci贸 Polit猫cnica de Catalunya, will incur a 300 € administration fee.

Discounts.
  • Discounts are non-accumulable. The greater discount of those requested will be applied.
  • Discounts can only be applied under prior application and approval.
  • Once registration has been confirmed, no discount will be applied.
  • Students are responsible for placing applications for any discounts.

Qualification. In order to obtain the Qualification/Diploma issued by the Polytechnic University of Catalonia, the student must be in possession of a recognised university qualification or internal university qualification equivalent to a degree or diploma. If this is not the case, the student will receive a certificate of completion for the course, issued by the Fundaci贸 Polit猫cnica de Catalunya. Students with outstanding payments due to the Fundaci贸 Polit猫cnica de Catalunya or who has not approved all the credits necessary to overcome the program before the date of completion of this program will not be eligible to receive any qualification, diploma or certificate.

Barcelona, October 31, 2017


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