Tracking the Economy Using FOMC Speech Transcripts
Laura Battaglia and Maria Salunina
Hear from faculty, admissions and career services officers, current students and alumni from our Data Science program
Watch the interactive videoAs data becomes easily available as never before, so too does its volume grow, and extracting useful quantitative insights becomes more and more challenging.
The curriculum will guide students from modeling and theory to computational practice and cutting edge tools, teaching skills that are in growing global demand.
Data Science Methodology students will be armed with a solid knowledge of statistical and machine learning methods, optimization and computing, and the ability to spot, assess, and seize the opportunity of data-driven value creation.
Students will learn how to apply classroom examples using real data and answering concrete business questions from the perspectives of different industries. Through an independent master's project and the opportunity for industrial practicum work conducted with local businesses, students can have the opportunity to solve actual analytics problems hands-on.
Our courses are taught by leading academics and researchers in the fields of Economics, Operations, and Statistics, as well as experienced professionals from the analytics industry. The program also invites guest speakers and entrepreneurs working at the frontiers of the Data Science.
Accenture sponsors a full scholarship for one student in the Barcelona GSE Data Science Methodology Program.
Scholarship criteria and details
The Data Science Center offers scholarships in the form of research assistantships (RAs) that require the student to be involved with the Center's data science projects.
About the Barcelona GSE Data Science Center
The Data Science Methodology Program is organized around four pillars:
In September, students are required to take two brush-up courses. Students who can provide evidence of sufficient past coursework may be exempt:
The course offer displayed is for next year's edition (2021-22). Course offer is subject to change.
Course list for current students (2020-21)
Course Title | Credits | Professor(s) |
---|---|---|
All courses are mandatory. | ||
Statistical Modelling and Inference | 6 | Omiros Papaspiliopoulos |
Deterministic Models and Optimization | 6 | Marc Noy Piotr Zwiernik |
Data Warehousing and Business Intelligence | 3 | Coordinator: Nandan Rao |
Computational Machine Learning I | 3 | |
Economic Methods for Data Science | 3 |
Course Title | Credits | Professor(s) |
---|---|---|
Mandatory | ||
Machine Learning | 6 | Gábor Lugosi |
Computational Machine Learning II | 3 | Vicenç Gomez |
Electives | ||
Financial Econometrics | 6 | Christian Brownlees |
Pricing Financial Derivatives (Part I and Part II) | 6 | Eulàlia Nualart |
Networks: Concepts and Algorithms | 3 | Joan de Martí |
Quantitative Methods of Market Regulation | 3 | Albert Banal |
Quantitative and Statistical Methods II | 6 | Joan Llull |
Course Title | Credits | Professor(s) |
---|---|---|
Mandatory | ||
Master Project | 6 | Coordinator: Joan Verdú |
Electives Note: This list is not exhaustive. Other electives will be available. |
||
Industrial Practicum Complements the master project with credits if student is placed in company working full-time |
6 | Subject to availability and selection process. Coordinator: Joan Verdú |
Stochastic Models and Optimization | 3 | Gergely Neu Hrvoje Stojic |
Networks: Models and Applications | 3 | Joan de Martí |
Text Mining for Social Sciences | 3 | Hannes Mueller Rubén Durante Nandan Rao |
Machine Learning for Finance | 3 | Argimiro Arratia |
Blockchain: From First Principles to Analytics | 3 | Coordinator: Gaston Besanson |
Digital Economy | 3 | Rosa Ferrer Juan-José Ganuza Antonio Penta |
Policy Lessons ** | 3 | Albert Bravo-Biosca Juan Francisco Jimeno |
** Requires some prerequisite knowledge and authorization of the program director. Availability depending on sufficient demand.
The master project is a required component of all Barcelona GSE Master's programs. Working individually or in groups, students use the tools and knowledge they've acquired during the entire year to explore a topic of their choice. A professor supervises throughout the project.
Examples of master projects from recent Data Science cohorts
Select a project to view a summary on the Barcelona GSE Voice, our student and alumni blog:
Laura Battaglia and Maria Salunina
Maximilian Muller
Aron Pap
Michele Costa, Laurits Marschall, Seyed Hamed Mirsadeghi, Alessandro de Sanctis, and Alessandro de Sanctis
Kwa Jie Hao
Upon successful completion of the program, students will receive a Master's Degree in Data Science awarded jointly by Universitat Autònoma de Barcelona (UAB) and Universitat Pompeu Fabra (UPF).
This official Master's Degree is in the process assessment by the Catalan and Spanish education authorities within the framework of the Bologna Process (in Spanish, “Master Universitario o Master Oficial”).
Data Science students usually come from backgrounds primarily in Economics, Physics and Engineering. Successful candidates have strong interest in becoming developers of Data Science methodologies and algorithms, they are committed to remain up to date with current scientific developments in the field and have real interest in both the foundations of the field and real-life and large-scale applications
The industrial practicum is an in-depth analytics project that takes place during the final three months of the master. The practicum gives Data Science students the opportunity to complete a "deep dive" analytics project using real data from selected companies around Barcelona.
Students will dedicate 300 hours to the practicum, collaborating with companies on-site using real data to solve a specific challenge that requires the types of "skill bundles" they have acquired during the first two terms of the master program.
Companies that have expressed interest in offering practicum projects to Barcelona GSE students include commercial banks, consulting firms, mobile application developers, risk analysts, and online retail platforms, among others. With a wide menu of companies competing for their attention, students are very likely to be matched with a practicum in the industry where they might prefer to work after graduation.
Some of the companies collaborating with the industrial practicum are:
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Sample practicum project titles
Examples of recent professional placements:
Company | Position | Industry | Location |
---|---|---|---|
Accenture | Analyst | Consulting | Barcelona |
Barcelona Supercomputing Center (BSC) | Data Scientist | Research | Barcelona |
Blackrock | Data Scientist | Consulting | London |
Central Bank of Chile | Head of Economic Surveys and Administrative Records | Government & Agencies | Santiago |
Criteo | Data Scientist | Advertising & Marketing | Paris |
ESADE | Research Assistant | Research & Academia | Barcelona |
European Central Bank (ECB) | Trainee | Government & Agencies | Frankfurt |
European Investment Bank (EIB) | Trainee | Government & Agencies | Luxembourg |
Fresenius Medical Care | Junior Data Scientist | Healthcare | Berlin |
International Labour Organisation (ILO) | Data Scientist | International Organizations | Geneva |
"la Caixa" Business Intelligence | Data Scientist | Banking & Finance | Barcelona |
Munich Airport | Data Scientist | Aviation | Munich |
Novartis | Advanced Analytics Specialist | Healthcare | Barcelona |
Socialpoint | Game Data Scientist | Gaming | Barcelona |
12 students from 7 countries (67% international)
Most represented countries this year:
Most common academic backgrounds:
Overview of Data Science career paths
To read personal career stories by Data Science alumni, visit the Data Science Program Ambassadors page.
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