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Master's degree in Artificial Intelligence

  • New offer
Modality
In-person
Branch of knowledge
Engineering and Architecture
School(s)
Higher Technical Engineering School
Rúa Lope Gómez de Marzoa, s/n, 15782
Santiago de Compostela
881816700 (Conserxaría)
881816701 (Dirección)
etse.secredireccion [at] usc.gal
Campus
Santiago de Compostela
Coordinator
María Jesús Taboada Iglesias
Contact
maria.taboada [at] usc.gal

The Master's degree in Artificial Intelligence (AI) focuses on university training in one of the areas that attracts most interest in the field of Computer Science, both from the scientific-academic point of view and in terms of its applications in multiple sectors of activity. In recent years, AI has undergone an exceptional development, motivated by the appearance of technologies that have meant a great advance in the discipline and by the availability of hardware resources that have made its application viable in different domains.

Duration: 2 academic years
RUCT code: 4317738
ECTS Number: 90
Seats number: 20

Dean or center director:
JULIA GONZALEZ ALVAREZ
julia.gonzalez [at] usc.es

Title coordinator:
María Jesús Taboada Iglesias
maria.taboada [at] usc.gal

Use languages:
English

Coordinator university:
University of A Coruña

Partaker universities:
University of Santiago de Compostela University of A Coruña University of Vigo

Xunta de Galicia title implantation authorization date:
Orde do 27/07/2022 (DOG do 10/08/2022)

BOE publication date:
BOE do 13/02/2023

Last accreditation date:
27/06/2022

Completion requirements:

Compulsory: 36
Optional: 36
External internships 6
Master’s Final Project: 12
Total: 90

Not contemplated

AI Project Management

  • P4251111
  •  
  • Compulsory Credits
  •  
  • Second Semester
  •  
  • 3 Credits

AI in Health

  • P4251131
  •  
  • Elective Credits
  •  
  • First Semester
  •  
  • 3 Credits

Intelligent IoT

  • P4251132
  •  
  • Elective Credits
  •  
  • First Semester
  •  
  • 3 Credits

Intelligent Cibersecurity

  • P4251133
  •  
  • Elective Credits
  •  
  • First Semester
  •  
  • 3 Credits

Process mining

  • P4251134
  •  
  • Elective Credits
  •  
  • Second Semester
  •  
  • 3 Credits

Intelligent Real-Time Systems

  • P4251135
  •  
  • Elective Credits
  •  
  • Second Semester
  •  
  • 3 Credits

Emergent and Entrepreneurial Aspects in IA

  • P4251136
  •  
  • Elective Credits
  •  
  • First Semester
  •  
  • 3 Credits

Work Placement

  • P4251112
  •  
  • Compulsory Credits
  •  
  • Work Placements in Companies for Degrees and Master's Degrees
  •  
  • 6 Credits

Among the skills desirable in students entering the training program of this Master's Degree, we can mention the following:

- Basic abilities in the management of new technologies.
- Abstraction, analysis, synthesis and local reasoning abilities.
- Ability to work in teams.
- Sense of organization, attention to detail and practical sense.
- Curiosity, imagination, creativity, innovation and entrepreneurial spirit.
- Interest in scientific and technological advances.

The following knowledge is recommended:

-Mathematics (analysis, linear algebra, geometry, basic statistics and probability).
-Programming, data structures and algorithms.
-Fundamentals of computer structure.

Completion requirements:

Compulsory: 36
Optional: 36
External internships 6
Master’s Final Project: 12
Total: 90

La USC, a través del ORE mantiene un sistema de información permanente a través de la web, que se complementa con campañas y acciones informativas específicas de promoción de las convocatorias. Además, cuenta con recursos de apoyo para el estudiantado de acogida, tales como la reserva de plazas en las Residencias Universitarias, o el Programa de Atención a Estudiantes Extracomunitarios (PATEX) del Vicerrectorado con competencias en movilidad, a través del cual voluntarios/as de la USC realizan tareas de acompañamiento dirigidas a la integración en la ciudad y en la Universidad del alumnado de acogida.

Se organiza una sesión de recepción, al inicio de cada cuatrimestre, en la que se les informa y orienta sobre el centro y los estudios, al tiempo que se les pone en contacto con los coordinadores académicos, que actuarán como tutores, y el personal del Centro implicado en su atención.

La ETSE, además de los responsables citados anteriormente, cuenta con la colaboración de varios docentes que actúan como coordinadores académicos, y cuya función es tutelar y asistir en sus decisiones académicas al alumnado propio y de acogida, así como firmar los acuerdos académicos de movilidad que aseguren que la acción se encuadre en los objetivos y competencias del título.

En la USC, además de las actividades indicadas antes, se ofrece una atención continuada. La dirección del centro y su Unidad de Apoyo a la Gestión están accesibles a diario para cualquier consulta de ámbito académico que afecte a los estudios de la Escuela.

El puesto de coordinación de los títulos es el enlace natural con el alumnado para apoyo y orientación relacionada con los estudios de grado o máster. El centro dispone de pantallas informativas donde se distribuye información de interés (anuncios, becas, empleo, jornadas, conferencias, etc.). Otros medios de información son los tableros, donde se publican horarios de clases, exámenes y otros anuncios (normativas, programas de movilidad, prácticas externas, etc.).

Además, la página Web del Centro se mantiene permanentemente actualizada como referencia básica de información, en la que se pueden consultar horarios de actividades académicas, calendarios de evaluación, programas de asignaturas, horas de tutoría del profesorado, actividades extraordinarias, normativa, etc. También dentro del Campus Virtual de la USC se habilitan aulas virtuales específicas para coordinación de los títulos, y que son un punto de encuentro entre profesorado y alumnado.

Access

Poderán acceder ás ensinanzas oficiais de máster:

1. As persoas que estean en posesión dun título universitario oficial español.
2. Aquelas que teñan un título expedido por unha institucion de educación superior do EEES que faculta no país expedidor do título para o acceso a ensinanzas de máster.
3. Os titulados conforme a sistemas educativos alleos ao EEES sen necesidade de homologación dos seus títulos, previa comprobación pola Universidade de que os ditos títulos acreditan un nivel de formación equivalente aos correspondentes títulos universitarios españois e que facultan no país expedidor do título para o acceso a ensinanzas de posgrao.

Admission

Modality: specific criteria

Degrees by order of preference:

1º) Graduates in Computer Engineering; Data Science and Engineering; Artificial Intelligence; Robotics; Telecommunications Engineering; Industrial Engineering; Mathematics; and Physics.

2º) Applications for admission from other degrees will be assessed by the Admissions Committee on the basis of the knowledge acquired in the recommended fields: mathematics; programming and computer fundamentals and structure.

Since the Master's Degree is taught entirely in English, students must demonstrate a minimum knowledge of English corresponding to level B1 (although B2 or higher is recommended) of the Common European Framework of Reference for Languages, under the terms determined by the Student Selection and Admission Committee.

ADMISSION CRITERIA

1º Adequacy of the degree to the contents of the Master's Degree (exclusive).
2º Academic record (max. 70%)
3º Work experience, extracurricular training, participation in related activities... (max. 30%)

Information is updated in each enrolment call

When an official degree is suspended, the USC guarantees the effective development of the studies that its students will begin until the end of the course. To this end, the Governing Council approves the criteria related, among others, to:

- The admission of new students to the degree programme.
- The gradual suppression of teaching.
- If the extinct degree is replaced by another similar one (modifying the nature of the degree), it establishes the conditions that facilitate students' continuity of studies in the new degree and the equivalences between the subjects of one and the other plan.

Modality: specific criteria

Degrees by order of preference:

1º) Graduates in Computer Engineering; Data Science and Engineering; Artificial Intelligence; Robotics; Telecommunications Engineering; Industrial Engineering; Mathematics; and Physics.

2º) Applications for admission from other degrees will be assessed by the Admissions Committee on the basis of the knowledge acquired in the recommended fields: mathematics; programming and computer fundamentals and structure.

Since the Master's Degree is taught entirely in English, students must demonstrate a minimum knowledge of English corresponding to level B1 (although B2 or higher is recommended) of the Common European Framework of Reference for Languages, under the terms determined by the Student Selection and Admission Committee.

ADMISSION CRITERIA

1º Adequacy of the degree to the contents of the Master's Degree (exclusive).
2º Academic record (max. 70%)
3º Work experience, extracurricular training, participation in related activities... (max. 30%)

Information is updated in each enrolment call

- Possess and understand knowledge that provides a basis or opportunity for being original in the development and/or application of ideas —usually in a research context.

- Students must know how to apply their acquired knowledge and their capacity of problem solving in new or uncommon surroundings. All of this, inside broader —or multidisciplinary— contexts associated with their study area.

- Students must be able to integrate knowledge and confront the complexity of making judgements from information which could be incomplete and limited. This information must include reflections about social and ethical responsibilities associated with the application of their study areas’ knowledge and judgements.

- Students must know how to clearly and unambiguously communicate their conclusions —and the knowledge and ultimate reasons that sustain them— to specialized and non-specialized public.

- Students must possess learning abilities that will allow them to continue studying, in a way which would be largely self-directed and autonomous.

- To maintain and extend theoretical approaches founded to allow the introduction and exploitation of new and advanced technologies in the field of Artificial Intelligence.
- To successfully address all stages of an Artificial Intelligence project.
- To search and select the necessary useful information to solve complex problems, handling with fluency the bibliographic sources of the field.
- Elaborate adequately and with certain originality written compositions or motivated arguments, write plans, work projects, scientific articles and formulate reasonable hypotheses in the field.
- Work in teams, especially multidisciplinary teams, and be skilled in time management, people management and decision making.

- Understanding and mastery of techniques for the processing of texts in natural language.
- understanding and mastery of the fundamentals and techniques of the semantic processing of linked, structured and unstructured documents, and the representation of their contents.
- understanding and knowledge of the representation and knowledge processing techniques through ontologies, graphs and RDF, as well as of their associated tools.
- To know the fundamentals and basic techniques of artificial intelligence and its practical application.
- Ability to design and develop intelligent systems through the application of inference algorithms, representation of knowledge and automatic planification.
- Ability to recognise those problems that may need a distributed architecture that is not preset during system design, that will be adequate for the implementation of intelligent multi-agent systems.
- Ability to understand the implications of the development of an explainable and interpretable intelligent system.
- Ability to design and develop safe intelligent systems in terms of integrity, confidentiality and robustness.
- Ability to have a deep knowledge of the basic principles and models of quantum computation and to know how to apply them to interpret, select, evaluate, model, and create new concepts, theories, uses and technological developments related to artificial intelligence.
- Ability for the construction, validation and application of a stochastic model of a real system from observed data and critical analysis of the results obtained.
-Ability for the analysis of a set of data and the selection and application of the most appropriate statistical inference and regression techniques for the acquisition of knowledge for decision making.
- Ability to understand, pose, formulate and solve problems that can be addressed through automatic learning models.
- Knowledge of the computer tools in the field of data analysis and statistical modeling, and ability to select the most appropriate one for problem solving.
- Understanding and mastery of the main techniques of automatic learning techniques, including those dedicated to the treatment of large volumes of data. Understanding and mastery of the fundamentals and basic techniques for the search and filtering of information in large data collections.
- Knowledge of computer tools in the field of automatic learning and ability to select the most appropriate one for problem solving.
- Knowledge of the process and tools for the processing and preparation of data from its acquisition or extraction, cleaning, transformation, loading, organization and access.
- To understand and assimilate the abilities and limitations of the current intelligent robotic systems, as well as of the technologies that support them.
- To develop the ability to select, design and implement strategies based on artificial intelligence to provide robotic systems, both individual and collective, with the necessary capabilities to perform their tasks properly according to the objectives and constraints that arise.
- Knowledge of the different fields of application of technologies based on AI and their capacity to offer a differentiating added value.
- Ability to face interdisciplinary environments and combine and adapt different techniques, extrapolating knowledge between different fields.
- Knowledge of the techniques that facilitate the organization and management of projects in AI real environments, the management of resources and planification of tasks in an efficient way, taking concepts of knowledge dissemination and open science into account.

- Express themselves correctly, both orally and in writing, in the official languages of the autonomous community.
- Master the oral and written expression and comprehension of a foreign language.
- Use the basic tools of information and communication technologies (ICT) necessary for the exercise of their profession and for lifelong learning.
- Develop for the exercise of a citizenship respectful of democratic culture, human rights and gender perspective.
- To understand the importance of the entrepreneurial culture and to know the means available to entrepreneurs.
- Acquire life skills and healthy habits, routines and lifestyles.
- Develop the ability to work in interdisciplinary or transdisciplinary teams, to offer proposals that contribute to sustainable environmental, economic, political and social development.
- Value the importance of research, innovation and technological development in the socioeconomic and cultural progress of society.
- Have the ability to manage time and resources: develop plans, prioritize activities, identify critical ones, establish deadlines and meet them.

Mobility

Student mobility is regulated through the “Regulation of inter-university exchange.” Exchange programs are managed through the International Relations Office, such as national exchange programs (SICUE) as well as Europeans (ERASMUS) and from outside the European Union (exchanges with Latin American countries or English-speaking countries):

Portal Internacional

Internships

The curriculum includes an external internships subject of 6 ECTS that can be taken in the 2nd or 3rd semester. This subject is specifically oriented to training in a real environment since the student is integrated in a company to perform tasks that involve the practical application of the knowledge acquired. The realization of these internships implies the previous signature of an agreement with the company.

The degree includes a final Master's Thesis of 12 ECTS. Students must correctly apply the knowledge and skills acquired to a project in the field of artificial intelligence. They must also present and defend the developments, results and conclusions of the work carried out before a specialized audience.

The faculty will attend to the students in individualized tutoring sessions dedicated to guidance in the study and resolution of doubts about the contents and work of the course.

The Master's degree will be taught mainly by professors from the Department of Electronics and Computer Science of the USC, the Department of Computer Science and Information Technology of the UDC and the Department of Electronics and Computer Science of the UVIGO.

The contents of this page were updated on 07.27.2022.