Master's Degree in Data Science: Data Science for Decision Making Program

Program Director

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Hannes Mueller

PhD, London School of Economics

IAE-CSIC and Barcelona GSE

Steering Committee

faculty

Christian Fons-Rosen

PhD, London School of Economics

UPF and Barcelona GSE - on leave
faculty

Omiros Papaspiliopoulos

PhD, Lancaster University

ICREA-UPF and Barcelona GSE

The demand for Data Scientists is exploding, driven by the increasing availability of data and the advance of machine learning. Data collection and analysis have become crucial components of decision making in today’s private and public organizations and many have started to develop specialized departments for this purpose.

The ability to extract, handle, and analyze large amounts of data is therefore a key skill on today’s job market.

However, gathering and summarizing data is not enough. Data science can only improve decision making with an understanding of how choices affect outcomes. Data Scientists must therefore increasingly combine standard tools in machine learning with an understanding of the causal relationships behind the data.

The Barcelona GSE Master's Program in Data Science for Decision Making integrates key elements from Data Science and Economics to give graduates the ability to deal with all types of data and make the correct inferences from it.

Students will be trained in the use of cutting-edge machine learning methods and of statistical models that will help them to provide effective data support in the decision-making process of any organization. Students will, for example, be able to extract information from the structure of social networks, satellite images, large libraries of digitized text, read and visualize data in maps and make sense of geo-localized information and time series data. They will also be able to use this data for forecasting and evaluate different policy options or business strategies through models built on an understanding of causal relationships.

Study with leading researchers and practitioners

Data Science for Decision Makers integrates different approaches from Data Science, Statistics, Econometrics and Economics in a unique program taught by leading academics in the fields of Economics, Operations, and Statistics, as well as experienced professionals from the analytics industry and public policy consultants.

Work with real data on interdisciplinary teams

Students learn with real data to solve decision-making problems hands-on through homework, applied training sessions, and an independent Master's project.

The collaborative environment of the program will expose students to working with colleagues from many different academic and professional backgrounds on interdisciplinary teams.

Is “Data Science for Decision Making” for you?

The Decision Making track is tailored to accommodate both recent graduates and those with work experience in private and public organizations. All students will benefit from a combination of training in programming, theoretical model techniques and hands-on applications which will allow them advance any decision making process in any organization. Students with work experience will be able to see the data in their own work environment with completely new eyes and realize the potential of untapped data resources like text and images.

Program schedule: 

The Data Science for Decision Making Program is organized around four pillars:

  • Statistics and Machine Learning
  • Econometrics and Causal Identification
  • Data Warehousing, Business Intelligence, and Text Mining
  • Economics Models and Optimization for Decision-Making

In September, students are required to take two brush-up courses in Mathematics and Statistics. Students who can provide evidence of sufficient past coursework may be exempt:

Course offer is subject to change.

Term 1 (September - December)

Course Title Credits Campus Professor(s)
All courses are mandatory.
Economics for Data-driven Decision Making 6 Bellaterra Caterina Calsamiglia
Foundations of Econometrics 6 Bellaterra Laura Mayoral
Ursula Mello
Computational Machine Learning I 3 Ciutadella

Joan Verdú

Computing for Data Science 3 Ciutadella

Joan Verdú

Term 2 (January - March)

Course Title Credits Campus Professor(s)
Mandatory courses:
Computational Machine Learning II 3 Ciutadella Joan Verdú
Machine Learning and Causal Inference 3 Ciutadella / Bellaterra Nandan Rao
Hanna Wang
Text Mining: Models and Algorithms 6 Bellaterra / Ciutadella Hannes Mueller
Omiros Papaspiliopoulos
Elective courses:
Analysis of Spatial Data and Images 3 Ciutadella André Groeger
Clement Gorin
Data Visualization 3 Ciutadella Ioannis Arapakis
Networks: Concepts and Algorithms 3 Ciutadella Joan de Martí
Pau Milán
Political Economy * 6 Ciutadella Ruben Enikolopov
Maria Petrova

Term 3 (April - June)

Course Title Credits Campus Professor(s)
Mandatory:
Master Project 6 Ciutadella Coordinator: Joan Verdú
Elective courses:
Advanced Techniques in Applied Economics: Text Analysis for Economics and Finance 3 Ciutadella Ruben Durante
Development Economics and Public Policy * 6 Ciutadella Gianmarco León-Ciliotta
Alessandro Tarozzi
Forecasting and Nowcasting with Text as Data 3 Ciutadella Christian Fons-Rosen
Hannes Mueller
Javier Perez
Intelligent Data Development 3 Ciutadella Laura Cozma, Margarita Triguero-Mas, Javier Mas Adell, Caterina Casamiglia
Networks: Models and Applications 3 Ciutadella Joan de Martí
Pau Milán

* Course requires authorization by the program director as it is shared with other Master's programs at the Barcelona GSE.


Master's degree awarded

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”).

Quality indicators


What skills and knowledge will I acquire in this program?
  • Ability to provide adequate data analysis for decision-making problems in research, governments, firms, international organizations and NGOs.
  • Ability to analyze the decision-making problem through the combination of applied data science and economics frameworks.
  • Programming skills necessary to extract data from any source including text, images, social networks, geocodes and maps.
    • Use and program cutting edge machine learning and econometric tools to analyze the resulting data.
    • Gain expertise in database management and distributed processing in a cloud computing environment.
    • Develop a deep understanding of the differences between correlation and causality and why this is crucial for optimal decision-making.
    • Communicate data analysis results effectively through presentation and aesthetic charting skills.
  • Ability to approach problems from different angles and to be aware of complementarities in knowledge on interdisciplinary teams.
Who will benefit from this program?

The goal of this Master's program is to serve two profiles:

  • The applied nature of the course aims to be accessible to students that have work experience in enterprises, government or international organizations and have worked with data inside these organizations.
  • The program gives recent graduates with strong analytical skills the possibility to specialize in applied data work.

Given the diverse background of our students, there are no prerequisites in either Data Science or Economics. However, students will only be able to absorb the wealth of methods that are taught with some experience of working with data, very strong quantitative skills, and some prior knowledge in Statistics.

Students will learn how to use STATA and program in Python during the Master's, but some experience in these two software packages will allow students to focus on the applications.

Who hires Data Science graduates?
  • Consulting Firms
  • Financial Services
  • Government & Authorities
  • International Organizations / Non-profits
  • Technology
  • Research & Academic Institutions
  • Other Industries

Faculty

Alumni

Build your career and your network

In addition to a track record of strong placements, the Barcelona GSE Master's programs offer access to a close-knit community of colleagues, mentors, and friends for life.

Your studies will be intense, but your academic environment doesn't have to be. Barcelona GSE programs foster a collaborative spirit among classmates and personal interaction with faculty.

This doesn't end on graduation day. Students in the Barcelona GSE Master's programs become lifelong members of the Barcelona GSE Alumni community, a thriving international network where they can connect socially and professionally for years to come.

winning team with trophy