Other profiles might be considered provided they guarantee solid foundations in Mathematics and Computer Science as to enable the candidate to follow the programme.
The master's degree in Data Science is offered to students from all over the world. Candidates must have a good comprehension, oral and written expression in English. Candidates must also be motivated to discover knowledge from data in the fascinating world of sciences and technologies.
Four semesters. (120 ECTS)
The curriculum of the FIB Master's Degree in Data Science was approved by the Faculty Board on 1st July, 2020. It is adapted to the European Higher Education Area (EHEA) and has a 120 ECTS credits:
The University Master's Degree in Data Science from the UPC is structured in 4 semesters. The first semester covers 30 compulsory ECTS; the second semester covers the remaining 24 compulsory ECTS and 6 elective ECTS; the third semester must cover the remaining 30 optional ECTS. The fourth and final semester is fully devoted to the master thesis.
Thus, the compulsory training requires 54 ECTS (equivalent to 9 subjects of 6 ECTS) divided into 3 fields:
The following is the presentation of the structure of the master's study plan:
The elective training is structured in 36 ECTS. The 36 ECTS must be completed from the following offered tracks:
The deep dive in specific aspects of Data Science track deepens in advanced aspects of data management and data analysis. The applications of Data Science for specific domains track focuses on Data Science techniques specific for popular domains of application, which require specific pre-processing, management and analysis of specific data. The deep dive track is meant to get specialized in advanced techniques, while the applications track is meant to get specialized in specific domains. Finally, the Innovation and Research track delves into the connection of Data Science with business innovation and research. Courses in the innovation and research track focuses on fostering the required traversal skills to meet the high level of innovation necessary in the professional field of Data Science.
Students can choose courses from the abovementioned tracks to fulfill the elective training. However, the following maximum of ECTS per track is set:
Accordingly, students must take at least 1 elective course from the deep dive track.
The admission period to start the Master programme in September 2021, is open from 25 February to 5 June, 2021.
The admission period is divided into two periods:
The notification from 11 June will include a waiting list with all the candidates whose position in the candidates list is higher than the number of places offered in the Master. The list will be ordered by candidates access mark. The candidates in that list can become admitted if some of the candidates firstly admitted decide to give up their seat.
Admitted candidates must accept their admission and confirm it with the payment of the allocation fee before 17 Juny, 2021. After that day, we will understand that they give up their seat, so their admission will be revoked and the place assigned to the following candidate in the waiting list.
The official list of accepted candidates will be published on 18 June, 2021, on the FIB website, in the "Enrollment" section of each Master programme.
Candidates must provide proof of their English proficiency, with at least a B2 level of the Common European Framework of Reference for Languages (or equivalent).
IMPORTANT: All documents issued outside Spain or in non-Spanish-speaking countries must be translated into Spanish or Catalan. Documents issued in countries that do not belong to the European Higher Education Area must be stamped and legalised by the appropriate government department.
The Academic Committee is in charge of the admission of the candidates. The criteria are: Academic Transcripts (60%), Relevance of the Bachelor (20%), Background and professional experience (5%) and Motivation Letter (15%).
For a successful development of the studies leading to the title of Master's Degree in Data Science taught at UPC, the admission profile must correspond to the following personal and academic characteristics:
Since Data Science sits in the confluence of Computer Science and Mathematics, the main recommended entry profiles are:
However, there are several other degrees that would allow to successfully pursue a master's degree in Data Science. Specifically, any degree that guarantees a solid knowledge in the Computer Science and Mathematical technical competences previously mentioned. For reference, the following degrees typically meet the expected technical competences:
Given the diversity of degrees in these areas, and since this master's degree does not consider training complements, the academic committee will check the bachelor syllabus of the applicant and assess whether the study plan followed adequately covers the Mathematics and Computer Science technical skills required in order to be admitted.
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