Master in
Fundamental Principles
of Data Science

Introduction
Objectives
Admission
Frequently Asked Questions

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.

Information:

  • Number of credits:  60
  • Mode of delivery:   Face to face
  • Specializations:  No
  • Places offered:  30
  • Approximate price:  27€ per credit (82€ for students who are not EU nationals and do not currently reside in Spain).
  • Qualification awarded: MSc in Fundamental Principles of Data Science (Official MSc Title)
  • Faculty or school:  Faculty of Mathematics and Computer Science
  • Coordination:  Jordi Vitrià i Marca
  • Information: sec.mat.inf@ub.edu
  • Submission of applications: February 5, 2024, to March 1, 2024
  • Webhttps://mat.ub.edu/sciencedata/

The Master’s Degree in Fundamental Principles of Data Science aims to provide the tools, knowledge and competences required to work effectively as a data scientist. The course focuses on the competences required to understand, modify and create algorithms, analytical and exploratory methods and techniques; as well as leadership abilities and the development of effective data-based projects.

Core subjects:

  • Numerical Linear Algebra
  • Optimization
  • Bayesian Statistics and Probabilistic Programming
  • Machine Learning
  • Agile Data Science
  • Presentation and Data Visualization
  • Ethical Data Science

Optional subjects:

  • Big Data
  • Deep Learning
  • Recommenders
  • Probabilistic Graphical Models
  • Business Analytics
  • Natural Language Processing
  • Computer Vision
  • Complex Networks
  • Data Science for Health
  • Time Series

Recommended applicant profile

The ideal applicant for this master’s degree holds a bachelor’s degree in computer science, mathematics, physics, statistics, or similar background, has a strong academic CV, and has an interest in the field of data science.

Applicants will be looking to work in data science in the corporate sector or in government bodies, and in sectors that require high-level specialists in data analysis, interpretation and visualisation, or to begin a research career focused on data analysis.

Regardless of their previous studies, students of this master’s degree should have basic knowledge of programming, calculus, algebra and statistics.

Basic admission requirements

In accordance with Article 16 of Royal Decree 1393/29 October 2007, students must hold one of the following qualifications to access university master’s degree courses:

  • An official Spanish degree.
  • A degree issued by a higher education institution within the European Higher Education Area framework that authorizes the holder to access university master’s degree courses in the country of issue.
  • A qualification from outside the framework of the European Higher Education Area. In this case, the qualification should be recognized as equivalent to an official Spanish degree. If it is not recognized, the University of Barcelona shall verify that it corresponds to a level of education that is equivalent to official Spanish degrees and that it authorizes the holder to access university master’s degree courses in the country of issue. Admission shall not, in any case, imply that prior qualifications have been recognized as equivalent to a Spanish master’s degree and does not confer recognition for any purposes other than that of admission to the master’s degree course.

Specific admission requirements

Applicants with the following qualifications may be admitted:

  • Holders of bachelor’s degrees in Computer Science, Mathematics, Physics, Statistics or related qualifications.
  • Holders of bachelor’s degrees in other subjects of similar background, with the authorisation of the Master’s Committee.

Given that the master’s degree is taught entirely in English, applicants must certify that they have at least level B2 English.

Enrollment

Submit your pre-enrollment application.  

 

 

When does the academic course start? The course starts in early September and ends in July.

Can I apply for studies if I am in the final year of my Bachelor’s degree? Yes, If you are in your final year of undergraduate degree studies, we will accept your application to the program. In case of being accepted, it will be conditional to finish your undergraduate program by mid-July.

What are the first steps required to study this university master’s degree course? The first stage is pre-enrolment; the master’s degree committee will then conduct its selection process.

What are the selection criteria? Applicants for this master’s degree course should hold an EHEA bachelor’s degree in computer science or mathematics or an equivalent qualification. A good academic record is also required and a particular interest in the field of data science. The goal of applicants should be to pursue a professional career in data science in a company or public administration, or in sectors that require specialists with a high level of training in data analysis, interpretation, and visualization (finance, biomedicine, information and communication technologies, etc.) or to start a research career in topics related to data analysis. Independently of the applicant’s bachelor’s degree, knowledge of programming, calculus, algebra, and statistics is required. Since the course is taught in English, applicants should also possess a sufficient level of comprehension to be able to follow the course in this language.

What qualifications do I need? Applicants need ONE of the following qualifications: (i) An official Spanish university degree; (ii) A university degree issued by a university regulated by the European Higher Education Area which would entitle the applicant to enroll on an equivalent master’s degree course in any other EHEA-regulated institution; (iii)  A university degree issued by a university outside the EHEA framework, although in this case, applicants must obtain either prior validation of their degree certificate or the University of Barcelona’s official, written recognition that their degree certificate adequately qualifies them for EHEA university master’s degree studies.  Successful admission does not qualify as recognition or validation of previous degrees, and in all cases, definitive admission will depend on the evaluation criteria set out by the University and the master’s degree committee. Applicants will typically have a strong academic background in Mathematics, Computer Science, Physics, and an engineering field. For more information see our Student Profiles.

I do not have a B2 certificate level, what can I do? Any English certificate equivalent to B2 is valid. Check here to see the equivalences. If you need a last-minute certificate you can contact here.

If I have a university qualification from outside Spain, how can I enroll(i) By having your degree officially accredited and recognized as being equivalent to its Spanish counterpart; (ii)  By authorization from the dean of the faculty where the course is being offered, by approval that the level of your academic studies corresponds to the level required of Spanish applicants, and by demonstrating that your qualification would entitle you to master’s degree level study in the country of issue.

How much does a university master’s degree course cost?  As an indication, fees for the academic year 2021-2022 were 27€ per credit (82€ for students who are not EU nationals and do not currently reside in Spain). All fees are officially regulated by the Catalan regional authorities (Generalitat de Catalunya), and supported by agreements made by the UB’s Governing Council and Board of Trustees.

What exactly are ECTS credits? The European Credit Transfer and Accumulation System of credits are the academic units of measurement used by the master’s degree program to evaluate student qualifications in the following types of learning activity: lectures and practical classes, hours of study outside class,  and seminars, assignments, practical assignments and project preparation and completion of examinations or other evaluative tests.

Is there an application fee? There is a 35 euro non-refundable application fee.

How can I apply for admission to a double master’s degree course? You have to apply to both master’s degree courses and if you are accepted on both of them, you will be eligible for the double master’s degree. Notice that the two Final Master Projects (FMP), one for each Master,  should be two different documents. Said that, we consider two different options. Either the two projects are “totally independent” and so each one will be defended in different committees (corresponding to each program), or the projects might share a common part plus differentiated specific chapter(s) corresponding to the aims of each master. In this case, the coordination of the FMPs of the two masters might consider a unique committee that will elaborate on two different and independent resolutions.

Do I need to translate my documents into English to apply? All supporting documents must be translated into Catalan, Spanish, or English.

Is there any financial aid or grant that I can apply for? Check the scholarships you can apply for here. Contact beca.estudis@ub.edu if you have any other questions regarding grants or financial support.

Can I do the master’s degree course on a part-time basis in order to combine a job and the master’s degree course? Yes, we offer the possibility to do the course on a part-time basis. The minimum number of credits per year is 30, with an estimated workload of 18 hours per week.

What about the language of the master’s degree course? The master’s degree course is taught in English.

Are there recommended itineraries?

Recommended itinerary, full-time MSc (1 year):

1st semester (30 ECTS):
572661 Computational Linear Algebra (6 ECTS, 1st Semester, Compulsory)
572664 Machine Learning (6 ECTS, 1st Semester, Compulsory)
572665 Agile Data Science (6 ECTS, 1st Semester, Compulsory)
572669 Deep Learning (3 ECTS, 1st Semester, Optional)
572662 Optimization (6 ECTS, 1st Semester, Compulsory)
572666 Presentation and Visualization (3 ECTS, 1st Semester, Compulsory)

2ond semester (30 ECTS):
572184 Bayesian Statistics and Prob. Prog. (3 ECTS, 2ond Semester, Compulsory)
574185 Ethical Data Science (3 ECTS, 2ond Semester, Compulsory)
572677 Master Thesis Project (12 ECTS, 2ond Semester, Compulsory)
+ 4 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)

Recommended itinerary, part-time MSc (2 years):

1st semester (15 ECTS)
572664 Machine Learning (6 ECTS, 1st Semester, Compulsory)
572665 Agile Data Science (6 ECTS, 1st Semester, Compulsory)
572669 Deep Learning (3 ECTS, 1st Semester, Optional)

2ond semester (15 ECTS)
572184 Bayesian Statistics and Prob. Prog. (3 ECTS, 2ond Semester, Compulsory)
574185 Ethical Data Science (3 ECTS, 2ond Semester, Compulsory)
+ 3 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)

3rd semester (15 ECTS)
572661 Computational Linear Algebra (6 ECTS, 1st Semester, Compulsory)
572662 Optimization (6 ECTS, 1st Semester, Compulsory)
572666 Presentation and Visualization (3 ECTS, 1st Semester, Compulsory)

4th semester (15 ECTS)
572677 Master Thesis Project (12 ECTS, 2ond Semester, Compulsory)
+ 1 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)

Key Details
Language:
English
Location:
Pl. Universitat
Requirements:
Python, B2 Certificate
Key Details
Language:
English
Location:
Pl. Universitat
Requirements:
Python, B2 Certificate

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.

Information:

  • Number of credits:  60
  • Mode of delivery:   Face to face
  • Specializations:  No
  • Places offered:  30
  • Approximate price:  27€ per credit (82€ for students who are not EU nationals and do not currently reside in Spain).
  • Qualification awarded: MSc in Fundamental Principles of Data Science (Official MSc Title)
  • Faculty or school:  Faculty of Mathematics and Computer Science
  • Coordination:  Jordi Vitrià i Marca
  • Information: sec.mat.inf@ub.edu
  • Submission of applications: February 5, 2024, to March 1, 2024
  • Webhttps://mat.ub.edu/sciencedata/

The Master’s Degree in Fundamental Principles of Data Science aims to provide the tools, knowledge and competences required to work effectively as a data scientist. The course focuses on the competences required to understand, modify and create algorithms, analytical and exploratory methods and techniques; as well as leadership abilities and the development of effective data-based projects.

Core subjects:

  • Numerical Linear Algebra
  • Optimization
  • Bayesian Statistics and Probabilistic Programming
  • Machine Learning
  • Agile Data Science
  • Presentation and Data Visualization
  • Ethical Data Science

Optional subjects:

  • Big Data
  • Deep Learning
  • Recommenders
  • Probabilistic Graphical Models
  • Business Analytics
  • Natural Language Processing
  • Computer Vision
  • Complex Networks
  • Data Science for Health
  • Time Series

Recommended applicant profile

The ideal applicant for this master’s degree holds a bachelor’s degree in computer science, mathematics, physics, statistics, or similar background, has a strong academic CV, and has an interest in the field of data science.

Applicants will be looking to work in data science in the corporate sector or in government bodies, and in sectors that require high-level specialists in data analysis, interpretation and visualisation, or to begin a research career focused on data analysis.

Regardless of their previous studies, students of this master’s degree should have basic knowledge of programming, calculus, algebra and statistics.

Basic admission requirements

In accordance with Article 16 of Royal Decree 1393/29 October 2007, students must hold one of the following qualifications to access university master’s degree courses:

  • An official Spanish degree.
  • A degree issued by a higher education institution within the European Higher Education Area framework that authorizes the holder to access university master’s degree courses in the country of issue.
  • A qualification from outside the framework of the European Higher Education Area. In this case, the qualification should be recognized as equivalent to an official Spanish degree. If it is not recognized, the University of Barcelona shall verify that it corresponds to a level of education that is equivalent to official Spanish degrees and that it authorizes the holder to access university master’s degree courses in the country of issue. Admission shall not, in any case, imply that prior qualifications have been recognized as equivalent to a Spanish master’s degree and does not confer recognition for any purposes other than that of admission to the master’s degree course.

Specific admission requirements

Applicants with the following qualifications may be admitted:

  • Holders of bachelor’s degrees in Computer Science, Mathematics, Physics, Statistics or related qualifications.
  • Holders of bachelor’s degrees in other subjects of similar background, with the authorisation of the Master’s Committee.

Given that the master’s degree is taught entirely in English, applicants must certify that they have at least level B2 English.

Enrollment

Submit your pre-enrollment application.  

 

 

When does the academic course start? The course starts in early September and ends in July.

Can I apply for studies if I am in the final year of my Bachelor’s degree? Yes, If you are in your final year of undergraduate degree studies, we will accept your application to the program. In case of being accepted, it will be conditional to finish your undergraduate program by mid-July.

What are the first steps required to study this university master’s degree course? The first stage is pre-enrolment; the master’s degree committee will then conduct its selection process.

What are the selection criteria? Applicants for this master’s degree course should hold an EHEA bachelor’s degree in computer science or mathematics or an equivalent qualification. A good academic record is also required and a particular interest in the field of data science. The goal of applicants should be to pursue a professional career in data science in a company or public administration, or in sectors that require specialists with a high level of training in data analysis, interpretation, and visualization (finance, biomedicine, information and communication technologies, etc.) or to start a research career in topics related to data analysis. Independently of the applicant’s bachelor’s degree, knowledge of programming, calculus, algebra, and statistics is required. Since the course is taught in English, applicants should also possess a sufficient level of comprehension to be able to follow the course in this language.

What qualifications do I need? Applicants need ONE of the following qualifications: (i) An official Spanish university degree; (ii) A university degree issued by a university regulated by the European Higher Education Area which would entitle the applicant to enroll on an equivalent master’s degree course in any other EHEA-regulated institution; (iii)  A university degree issued by a university outside the EHEA framework, although in this case, applicants must obtain either prior validation of their degree certificate or the University of Barcelona’s official, written recognition that their degree certificate adequately qualifies them for EHEA university master’s degree studies.  Successful admission does not qualify as recognition or validation of previous degrees, and in all cases, definitive admission will depend on the evaluation criteria set out by the University and the master’s degree committee. Applicants will typically have a strong academic background in Mathematics, Computer Science, Physics, and an engineering field. For more information see our Student Profiles.

I do not have a B2 certificate level, what can I do? Any English certificate equivalent to B2 is valid. Check here to see the equivalences. If you need a last-minute certificate you can contact here.

If I have a university qualification from outside Spain, how can I enroll(i) By having your degree officially accredited and recognized as being equivalent to its Spanish counterpart; (ii)  By authorization from the dean of the faculty where the course is being offered, by approval that the level of your academic studies corresponds to the level required of Spanish applicants, and by demonstrating that your qualification would entitle you to master’s degree level study in the country of issue.

How much does a university master’s degree course cost?  As an indication, fees for the academic year 2021-2022 were 27€ per credit (82€ for students who are not EU nationals and do not currently reside in Spain). All fees are officially regulated by the Catalan regional authorities (Generalitat de Catalunya), and supported by agreements made by the UB’s Governing Council and Board of Trustees.

What exactly are ECTS credits? The European Credit Transfer and Accumulation System of credits are the academic units of measurement used by the master’s degree program to evaluate student qualifications in the following types of learning activity: lectures and practical classes, hours of study outside class,  and seminars, assignments, practical assignments and project preparation and completion of examinations or other evaluative tests.

Is there an application fee? There is a 35 euro non-refundable application fee.

How can I apply for admission to a double master’s degree course? You have to apply to both master’s degree courses and if you are accepted on both of them, you will be eligible for the double master’s degree. Notice that the two Final Master Projects (FMP), one for each Master,  should be two different documents. Said that, we consider two different options. Either the two projects are “totally independent” and so each one will be defended in different committees (corresponding to each program), or the projects might share a common part plus differentiated specific chapter(s) corresponding to the aims of each master. In this case, the coordination of the FMPs of the two masters might consider a unique committee that will elaborate on two different and independent resolutions.

Do I need to translate my documents into English to apply? All supporting documents must be translated into Catalan, Spanish, or English.

Is there any financial aid or grant that I can apply for? Check the scholarships you can apply for here. Contact beca.estudis@ub.edu if you have any other questions regarding grants or financial support.

Can I do the master’s degree course on a part-time basis in order to combine a job and the master’s degree course? Yes, we offer the possibility to do the course on a part-time basis. The minimum number of credits per year is 30, with an estimated workload of 18 hours per week.

What about the language of the master’s degree course? The master’s degree course is taught in English.

Are there recommended itineraries?

Recommended itinerary, full-time MSc (1 year):

1st semester (30 ECTS):
572661 Computational Linear Algebra (6 ECTS, 1st Semester, Compulsory)
572664 Machine Learning (6 ECTS, 1st Semester, Compulsory)
572665 Agile Data Science (6 ECTS, 1st Semester, Compulsory)
572669 Deep Learning (3 ECTS, 1st Semester, Optional)
572662 Optimization (6 ECTS, 1st Semester, Compulsory)
572666 Presentation and Visualization (3 ECTS, 1st Semester, Compulsory)

2ond semester (30 ECTS):
572184 Bayesian Statistics and Prob. Prog. (3 ECTS, 2ond Semester, Compulsory)
574185 Ethical Data Science (3 ECTS, 2ond Semester, Compulsory)
572677 Master Thesis Project (12 ECTS, 2ond Semester, Compulsory)
+ 4 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)

Recommended itinerary, part-time MSc (2 years):

1st semester (15 ECTS)
572664 Machine Learning (6 ECTS, 1st Semester, Compulsory)
572665 Agile Data Science (6 ECTS, 1st Semester, Compulsory)
572669 Deep Learning (3 ECTS, 1st Semester, Optional)

2ond semester (15 ECTS)
572184 Bayesian Statistics and Prob. Prog. (3 ECTS, 2ond Semester, Compulsory)
574185 Ethical Data Science (3 ECTS, 2ond Semester, Compulsory)
+ 3 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)

3rd semester (15 ECTS)
572661 Computational Linear Algebra (6 ECTS, 1st Semester, Compulsory)
572662 Optimization (6 ECTS, 1st Semester, Compulsory)
572666 Presentation and Visualization (3 ECTS, 1st Semester, Compulsory)

4th semester (15 ECTS)
572677 Master Thesis Project (12 ECTS, 2ond Semester, Compulsory)
+ 1 optional courses to be chosen among:
572676 Time Series Analysis (3 ECTS, 2ond Semester, Optional)
572675 Complex Network Analysis (3 ECTS, 2ond Semester, Optional)
572672 Business Analytics (3 ECTS, 2ond Semester, Optional)
572667 Big Data (3 ECTS, 2ond Semester, Optional)
574186 Data Science for Health (3 ECTS, 2ond Semester, Optional)
572671 Probabilistic Graphical Models (3 ECTS, 2ond Semester, Optional)
572673 Natural Language Processing (3 ECTS, 2ond Semester, Optional)
572670 Recommenders (3 ECTS, 2ond Semester, Optional)
572674 Computer Vision (3 ECTS, 2ond Semester, Optional)