Online University Master's Degree in Computational Engineering and Mathematics (joint URV, UOC)

Final Master's Degree Project

The University Master's Degree in Computational and Mathematical Engineering concludes with the preparation of a final project of 18 ECTS credits.

In order to enrol on this course, students must have already passed, or currently be enrolled on (during the same year as the final project), the 42 credits corresponding to the master degree's other courses. The specific prior knowledge required will depend on the final project's subject area.

The final project consists of performing an individual project, product, report and/or study that synthesizes the knowledge acquired in the programme's other courses. This is a compulsory course that students must take in order to complete the programme and is intended to assess the competencies associated with the degree. 

Computational and Mathematical Engineering students have the option of doing their final project on different subject areas proposed by the master degree's teaching staff. The available areas can be viewed in the course plan. Students must select the field of knowledge in which they want to perform their final master's degree project and submit an application, which must be accepted by the final project's supervisor and the programme's teaching staff. 

The final project is done individually, with tutoring and guidance from the final project supervisor, who provides the necessary support to ensure its successful completion. The final project's supervisor is responsible for guiding the student and monitoring the project's progress, and provides advice on each of the following aspects: conceptualization, rationale, methodology, reporting of the results and defence. The time spent by the student on the project is determined by the credits allocated to this course, with each credit being equivalent to 25 hours' work by the student. 

The final project concludes with a defence, in which students must make an asynchronous, online presentation (video) to a three-member assessment committee. The video should summarize the results obtained and the project's development.

Some examples of final projects submitted for the master's degree are listed below:

• An open-source development environment for Self-driving vehicles

• Análisis de datos clínicos en una Unidad de Cuidados Intensivos

• Aprendizaje supervisado en conjuntos de datos no balanceados con redes neuronales artificiales

• Impact evaluation of clustering-based k-anonymity for recommendations

• Jerarquías emergentes en redes complejas

• Metaheuristic algorithms for solving the multi-depot arc routing problem

• Simulación de sistemas flexibles: el caso del aerogenerador

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• Simulation of the mechanical behaviour of a historical church

• Solució d'alt rendiment per a química computacional

• Tecnologías que mejoran la privacidad en los sistemas de recomendación

• The center-focus and ciclicity problems: an implementation of the Lyapunov method and the interpolation technique

Duration

The Joint University Master's Degree in Computational and Mathematical Engineering has been designed so that it can be completed in one year (two semesters) or two years (four semesters), but there is no maximum time limit for completion of the degree. Each student can adapt the duration and pace of study to the time they have available to dedicate to them.

The student can choose, on an annual basis, the number of subjects of each semester in which he wants to enroll.In fact, when enrolling on courses, students receive personalized advice from their tutor to help them draw up a suitable plan. Aspects such as their needs, interests, time available and prior knowledge are all taken into account. The aim is to consolidate their skills, which will ensure that they make good progress while studying for the degree.

Students are recommended to take the master's degree in two years, particularly if they have to combine their studies with other endeavours. Taking the programme in one year is only recommended if the student can study full-time.

Prior studies assessment

The prior studies assessment is the procedure that students must request if they wish to validate the courses they have completed at the UOC or any other university.

It is not a mandatory procedure. To request the prior studies assessment, only the last adapted academic record is considered valid.

The result of students' prior studies assessment is valid provided they have an open academic record at the UOC. It will be valid for newly admitted students if they enrol on the semester immediately following application for the procedure. Otherwise, their prior studies assessment will expire and they will have to repeat the procedure.

The prior studies assessment is carried out by a committee chaired by the Vice President for Teaching and Learning and whose members are the directors of the UOC's programmes. The secretary's duties are performed by the person responsible for the procedure at the Secretary's Office. The committee's tasks are to evaluate and propose validations, adaptations and recognition of free elective credits.

Competencies

Joint University Master's Degree in Computational and Mathematical Engineering (URV, UOC) graduates will be able to:

• Understand and apply advanced computing knowledge and numerical or computational methods to engineering problems.
• Apply computational, mathematical and statistical methods to model, design and develop applications, services, intelligent systems and knowledge-based systems.
• Apply mathematical and computational methods to solve technological problems and company engineering problems, particularly in research, development and innovation tasks.
• Ability to model problems using the language of mathematics and solve them with formal reasoning.
• Identify the mathematical theories needed to construct models based on problems from other disciplines.
• Handle mathematics and statistics software.
• Synthesize and present research results verbally and in writing, in accordance with the rules for writing scientific documentation.
• Model, simulate and analyse systems, processes and networks.
• Analyse and process data that enable the generation and management of useful information during decision-making procedures.
• Design, implement and validate algorithms using the most suitable structures.
• Develop a research project proposal using research support tools.
• Understand and apply advanced knowledge in high-performance computing and, specifically, in parallel/distributed computing, to solve scientific and engineering problems.