General information

Academic year: 2022/2023

Level: Master

Type: Official Master's Degree

ECTS Credits: 60

Programme orientation Research

Length of programme (full time): 1 YEAR

Mode of delivery: Face-to-face

Level of qualification: Máster (MECES level 3 - EQF level 7)

Model of study: Full-time (42-60 ECTS per school year)

Work placement: Yes

Language(s) of instruction Spanish

More info: programme website

Programme coordinator


Field(s) of education and training (ISCED-F)

  • Software and applications development and analysis (0613)


Students who have completed the second cycle have the following competences:
– They possess and understand knowledge that provides a basis or opportunity for originality in the development and/or application of ideas, often in a research context.
– They are able to apply their acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.
– They are able to integrate knowledge and deal with the complexity of making judgements on the basis of incomplete or limited information, including reflections on the social and ethical responsibilities linked to the application of their knowledge and judgements.
– They know how to communicate their conclusions, and the knowledge and ultimate reasons behind them, to specialist and non-specialist audiences in a clear and unambiguous way.
– They possess the learning skills to enable them to continue studying in a largely self-directed or autonomous manner.

Programme qualification

Name of title awarded in original language

Máster Universitario en Ciencia de Datos e Ingeniería de Computadores

Qualification requirements

60 minimum credits

Programme courses

Course NameYearPeriod
Advanced Data Mining 1st Year 2nd Semester
Big data 1 1st Year 2nd Semester
Big Data 2 1st Year 2nd Semester
Bio-Inspired Vision Systems 1st Year 2nd Semester
Computational Biology with Big Data Omics and Biomedical Engineering 1st Year 1st Semester
Computational Neuroscience and Neuroengineering 1st Year 1st Semester
Computer Vision 1st Year 2nd Semester
Data Mining: Pre-Processing and Classification 1st Year 1st Semester
Data Mining: Unsupervised Learning and Fault Detection 1st Year 1st Semester
Data Science Applications and Intelligent Technologies 1st Year 2nd Semester
Embedded Systems and Hw/Sw Co-Design 1st Year 1st Semester
Entrepreneurship and Knowledge Transfer 1st Year 2nd Semester
High Performance Architecture for Vision 1st Year 2nd Semester
High Performance Computing for Classification and Optimisation 1st Year 2nd Semester
High Performance Signal Processing in Biomedicine 1st Year 2nd Semester
Image Feature Extraction 1st Year 1st Semester
Information Retrieval and Recommendation Systems 1st Year 2nd Semester
Internet of Things 1st Year 1st Semester
Introduction to Computer Engineering Programming 1st Year 1st Semester
Introduction to Data Science 1st Year 1st Semester
Introduction to Information Science Programming 1st Year 1st Semester
Master's Dissertation 1st Year 2nd Semester
Mechatronics and Aerospace Systems 1st Year 2nd Semester
Mobile Robotics and Neurobiotics 1st Year 2nd Semester
Probabilistic Graphical Models 1st Year 2nd Semester
Process Mining 1st Year 2nd Semester
Research Methodology 1st Year 1st Semester
Safe Servers 1st Year 1st Semester
Social Media Mining 1st Year 2nd Semester
Soft Computing Techniques for Learning and Optimisation. Neural Networks and Metaheuristics, Evolutionary and Bio-Inspired Programming 1st Year 2nd Semester
Soft Computing: Fuzzy Sets and Systems 1st Year 1st Semester
System Modelling and Time Series Prediction 1st Year 2nd Semester
Time Series and Data Flow Mining 1st Year 2nd Semester
Web Server Engineering 1st Year 1st Semester


Specialisation name

– Computer and Network Engineering
– Data Science and Intelligent Technologies

Admission information

Access to Master’s Degree programmes is granted to holders of:
A.1. A Spanish official university degree.
A.2. A degree issued by a Higher Education institution from another European Higher Education Area Member State which allows access to Master Degree’s programmes in that State.
A.3. A degree from a non-EHEA education system, upon verification by the Spanish University that the aforementioned degree accredits an equivalent education level to that of a Spanish university degree and allows access to postgraduate programmes in the issuing country.
A.4. A Spanish Bachelor in Advanced Artistic Education.
A.5. Official Spanish university degrees of Diplomado, Arquitecto Técnico, Ingeniero Técnico, Licenciado, Arquitecto, Ingeniero, Graduado or Máster Universitario.

Specific admission requirements

Access to this Master’s degree programme is granted to holders of a Spanish official university degree of Licenciado or Graduado (Bachelor’s degree), Ingeniero Superior and Ingeniero Técnico (Bachelor’s degree), or equivalent degrees from other education systems, in the fields of Computer Engineering, Telecommunications, Electronics, Physics, Mathematics, and Statistics. Access is also granted to graduates from other Engineering degree programmes who can demonstrate prior knowledge in computer science, communications and/or mathematics.

General regulations

Grading scale
In the Spanish university system, modules/courses are graded on a scale of 0 to 10 points with the following qualitative equivalence:
0-4,9: «suspenso»; 5-6,9: «aprobado»; 7-8,9: «notable»; 9-10: «sobresaliente». A special mention, «Matrícula de Honor» may be granted to up to 5% of the students in a group provided they have got a «sobresaliente». To pass a module/course is necessary to get at least 5 points.
In cases of recognition of ECTS, professional experience, cultural or sports activities, or student representation no grading will be recorded but, where appropriate, the word «Apto».


UGR Examination Regulations


More info on academic regulations at:

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