Master's Degree in the
Foundations of Data Science


PROVISIONAL LIST OF PERSONS ADMITTED IN THE SELECTION PROCESS






The master’s degree Foundations of Data Science provides students with the algorithmic and mathematical basis needed for the correct modelling and analysis of data through practical oriented sessions, as well as the professional skills necessary to tackle data-based projects. In the course, the emphasis is placed on skills related to understanding the foundations of the algorithms behind data science and to modifying and creating specific new algorithms tailored to the needs of data projects.
The master’s degree course includes topics ranging from numerical linear algebra, optimization and probabilistic programming, to machine learning, deep learning, complex networks, and recommender techniques. It also covers the application of these to natural language processing, temporal series and information extraction from images, using technologies capable of storing and processing large volumes of data: “big data”.

Academics

Schedule:

Monday - Friday 3pm - 7pm

Total study load:

60 ECTS-credits

Pricing:

The approximate price is 140 euros for enrolment, plus 46.50 euros per ECTS credit for EU nationals and Spanish residents, or 82 euros per ECTS credit for all other students.

Language:

English

Estimated workload:

Full time: 40 hours per week (including lectures and private study).

Part time: from 18 hours per week (including lectures and private study).

Application:

From 15 February to 27 April 2018

Admission results on May 23rd, 2018


Skills and competences

  • To understand the process of data valorization and its role in decision making.
  • To learn to clean and massage data with the goal of creating valuable, manageable, and informative datasets.
  • To learn to hypothesize and develop intuition about a dataset using exploratory analysis techniques.
  • To apply analytic and predictive machine learning efficiently and effectively.
  • To understand, create, and modify analytic and exploratory algorithms operating over data.
  • To verify and quantify the validity of a hypothesis using data analytics.
  • To learn to gather and extract information from structured and non-structured data sources.
  • To learn to use storage and processing technologies for handling large datasets.
  • To understand, create, and modify analytic and exploratory algorithms operating over data.
  • To verify and quantify the validity of a hypothesis using data analytics.
  • To communicate results using appropriate communication skills and visualization tools and techniques.
  • To know the privacy and data protection legislation, and the data scientist professional code and ethics.

CAMPUS


Located in the city centre, the Faculty of Mathematics and Computer Science is found in the Historic Building of the University of Barcelona, in Plaça de la Universitat.



Edifici Històric de la Universitat de Barcelona,
Gran Via de les Corts Catalanes 585,
08007, Barcelona

STUDENTS

Academic Bacgrounds

With the support of:

Supporters

Any question?

Please check this FAQ page as your question may have already been answered.
If you have any other question, please write us at master.fds@ub.edu