Applications are now closed.
Registration has ended for the 2016 edition of this program.
New for Summer 2016
The course will provide:
The Data Science toolbox (8 hours)
This will be a hands-on session where a range of tools commonly used in Data Science will be introduced.
Introduction to Machine Learning for Recommender Systems (6 hours)
Advanced Data Science and Machine Learning Topics (6 hours)
Alexandros Karatzoglou is a Senior Research Scientist at Telefonica Research working on Machine Learning. Alexandros received his PhD in Machine Learning from the Vienna University of Technology (TUWIEN). During his PhD he was a frequent visitor to the Statistical Machine Learning group at the ANU/NICTA in Canberra Australia. He has over 40 papers in the field and has won 3 best paper awards at the ACM RecSys and ECMLPKDD conferences. He has developed several ranking techniques for collaborative filtering, context-aware recommendation methods and techniques for recommendations in a social network. He is also the author of the core machine learning R package kernlab, and enjoys giving lectures on Machine Learning, Recommender Systems and R.
Hrvoje Stojic is a PhD candidate at UPF (GPEFM). He is also an alum of the Barcelona GSE Master's in Economics. His main research interest is to understand cognitive processess that underlie human learning and decision making, and how these processes might be employed by the brain. This is an interdisciplinary topic that spans several disciplines and in his work he relies on research that comes from fields like economics, psychology, artificial intelligence and neuroscience. In his research he uses mathematical modeling and develop behavioural experiments to evaluate model predictions. He has visited both the ABC group at the Max Planck Institute for Human Development in Berlin and University College London.
The course includes hands-on sessions where the methods introduced will be applied on real-world datasets. The course will also include homework assignments after each session. These assignments will be in a form of programming exercises where participants will implement algorithms learned in the classes.
The summer school focuses on implementing the algorithms taught in the class through hands-on sessions and homework assignments. Therefore, it is important to setup your computing environment to prepare for the summer school.
Each participant is expected to have access to a laptop or personal computer to carry out the computing assignments of the program.
Participants are encouraged to use a Unix-based operating system. These include all versions of Linux and Mac operating systems. Windows users are encouraged to install a partition or a virtual machine with a Linux distribution (for example, Ubuntu or Fedora operating system). A large portion of the tools are designed for Unix/Linux systems and working in such an environment is significantly easier.
All participants should install the following programs before the summer school starts. They are very common and it should be easy to find information on Internet on how to install them on your computer with your specific operating system.
Participants using Windows machines should in addition install the following programs:
We will provide students with a virtual server where all the tools are guaranteed to work. For this we will use Amazon Web Services (AWS), one of the leading providers of cloud computing services. Instead of using their personal computers, participants can use the virtual server to do the computing tasks. A requirement for this is to have an account at AWS, and participants are expected to have an account before the program starts. We will also use AWS to demonstrate how to easily scale up your computing tasks with cloud computing.
Participants are highly encouraged (although not required) to familiarize themselves somewhat with Python, R, and MySQL before the course.
There is limited space in the Barcelona GSE Summer School Courses. Among the candidates who meet the eligibility criteria, the Barcelona GSE will select those with more outstanding professional and/or academic careers.
Interested candidates should apply before May 30. After this deadline, your place may not be guaranteed. Capacity of the courses is limited. Some courses may close before May 30 depending on demand.
Applications will be evaluated by the program directors and candidates will be informed of their decision. A document will be attached to our response with payment information. Before applying, please read through the summer school cancellation policy and other regulations.
A wide range of short-term accommodation is available near campus for Barcelona GSE Summer School participants. Students and participants can take advantage of discounted offers by booking accommodation with one of our housing partners. These partners will be able to provide various affordable accommodation options tailored to suit different needs, including: flats, hostels and hotels, shared apartments, and student halls.
For more information, see the "Discounts" section of our accommodations page.
At the conclusion of the Summer Schools, participants will receive a certificate for the number of hours attended. All Barcelona GSE courses require an average of twice the lecture hours for readings, pre-readings and class preparation. Interested students should check with their universities to see if these hours are transferable into ECTS credits.
Fees listed are for the 2016 edition.
|Price for each course|
|Regular Fee||1800 €|
|Reduced Fee*||1000 €|
Discounts for registration in more than one course:
|Number of courses||Discount applied|
|2 courses||25% discount|
|3 courses||35% discount|
|4 courses||45% discount|
Notes about Summer School fees: