The master’s degree Fundamental Principles 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”.
Master's Degree in the
Fundamental Principles of Data Science
1st Application period for 2022-23 course starts on February 14, 2022, and ends on March 16, 2022
Apply for Admission
Academics
Schedule:
Monday - Friday 3pm - 7pm
Total study load:
60 ECTS-credits
Pricing:
The approximate price is 140 euros for enrolment, plus 27 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:
- February 14, 2022, to March 16, 2022
- Publication of the list of eligible/ineligible students: March 23, 2022
- Publication of decision on Masters’ accepted students: April 6, 2022
Grants:
The Accenture Analytics Career Path Scholarship is offered to enrolled students in this Master's Degree.
The scholarship includes:
- - All tuition fees for the master program.
- - Industrial Practicum (paid internship) at the Accenture Analytics Innovation Center during the academic year.
Selection criteria:
- Academic background
- Interest in working as a data scientist in a consulting firm
- All Master's applicants that show their interest in the Accenture Analytics Career Path Scholarship will be considered.
- Finalists will be contacted with detailed instructions regarding additional materials and steps in the scholarship selection process.
Check others scholarships you can apply for here. Contact beca.estudis@ub.edu if you have any other questions regarding grants or financial support.
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
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If you have any other question, please write us at master.fds@ub.edu