Introduction

Large amounts of data are generated in many aspects of personal and professional life, from electronic purchases to research or finances. If these data are not monitored or interpreted, they have no value. Data science is a new professional area that aims to give these data meaning by analyzing and interpreting them. A data scientist is a new professional profile at the intersection between maths and computer science. The master’s degree in Fundamental Principles of Data Science aims to provide, through theoretical and practical training, the algorithmic and mathematical bases for correct modeling and analysis of data, and the professional competencies to face data-based projects. There is a focus on competencies to understand the principles of algorithms that lie behind data science. Students will develop the ability to modify algorithms and create new ones, to adapt to the specific needs of a problem. Consequently, the course includes aspects that cover a wide area: computational algebra, optimization or probabilistic programming, automatic learning techniques and deep learning, complex networks, recommendation systems, applications to natural language processing, time series, extraction of information in images, and support for infrastructures that process big data.

Basic data

  • Number of credits:  60
  • Mode of delivery:   Face to face
  • Specializations:  No
  • Bridging Courses:  Yes
  • Places offered:  30
  • Approximate price:  46,50€ per credit ( 82 euros for students who are not EU nationals and do not currently reside in Spain). Fees for the academic year 2020-2021
  • Qualification awarded: MSc in Fundamental Principles of Data Science
  • Faculty or school:  Faculty of Mathematics and Computer Science
  • Coordination:  JORDI VITRIA MARCA

Accenture Data Science Scholarship

  • Accenture sponsors a full scholarship for one student in the UB Fundamental Principles of Data Science Program.

Is this the right program for you?

  • We welcome students from different disciplines. The ideal candidates have graduated in programs with a solid mathematical basis, e.g. computer science, statistics, mathematics, physics, or engineering.