University Master's degree in Machine Learning
Specialise in the area of greatest impact within Artificial Intelligence: machine learning. Learn to design and programme algorithms that enable machines to learn from data, solve complex problems, and generate solutions that improve decision-making in key sectors (healthcare, industry, retail, automotive, logistics, marketing, etc.).
- Language: English (level B2)
- Credits: 60 ECTS
- Duration: 1 academic years (2 terms)
- Spaces available: 20
- Modality: in-person
- Academic Director: Mikel Galar
- Faculty or School: Higher Technical School of Industrial and ICT Engineering
- Where lessons take place: Pamplona
- Information leaflet (pdf)
Presentation
Master’s degree in line with the Sustainable Development Goals of the UN 2030 Agenda.
Why should you study the University Master's degree in Machine Learning?
- High professional demand: You'll be part of one of the most sought-after and well-paid roles in sectors such as industry, ICT, finance, commerce, healthcare, agri-food, tourism, among others.
- Participation in real projects and strategic alignment: You will have the opportunity to collaborate on industry transfer projects within the Institute of Smart Cities (ISC) at UPNA and undertake internships in companies, applying your knowledge to solve real-world problems. This master's programme is aligned with the Smart Specialisation Strategy S4 of Navarre, with a focus on digitalisation and artificial intelligence.
- Academic Excellence: You will be taught by highly regarded faculty, supported by their teaching and research experience.
- You will acquire advanced skills in machine learning and deep learning, delving into:
- The theoretical and practical foundations of Machine Learning and Deep Learning
- The three main application fields of the Deep learning models: computes vision, natural language processing and time series
- The design, development and implementation of AI projects
- The full life cycle of a Machine Learning model
- Programming frameworks such as PyTorch and TensorFlow.
- The latest advancements within the AI field through reading scientific papers and their implementation
- You will have the skills to:
- Solve specific computer vision problems, natural language processing, and time series analysis, among others through advanced Machine Learning techniques.
- Design, implement, train and develop AI models.
- Master key frameworks such as PyTorch and TensorFlow
- Adapt Deep Learning architectures and models to specific problems, including fine-tuning large language models (GPT, LLma, Mistral, etc.).
- Evaluate artificial intelligence models and identify their technical and operational limitations.
- Research, compare, and develop state-of-the-art algorithms, and effectively communicate the results.
- Design research that addresses real-world or academic problems and propose critical, practical solutions.
- Collaborate and integrate into multidisciplinary teams in both workplace and research environments.
You can do this master's with:
Specialization
Training in competencies
Languages
Which degrees may grant me access to the Master's Degree in Machine Learning?
- Degree or Bachelor's degree in Computer Science (priority access)
- Degree or Bachelor's degree in Data Science (priority access)
- Other Bachelor's degrees related, such as Software Engineering or Data Engineering and Artificial Intelligence
Support for students
Which job positions can I access once I finish the Master's degree in Machine Learning?
- Machine Learning or Artificial Intelligence engineer
- Data scientist
- Technology consultant
- AI and Machine Learning researcher
- Team leader: Head of the Data Science area in companies from various sectors
- Managing positions: Chief Technology Officer (CTO) of Research (CRO) or Innovation (CINO)
- You will be able to apply your knowledge to:
- Tech start-ups, either by creating your own or joining projects based on artificial intelligence.
- Companies developing AI in-house, from creative and digital sectors to traditional industries.
- SMEs, helping them solve their specific needs through AI solutions.
- Large tech companies (Big Tech), becoming part of leading global teams.
- Technology centres and universities, contributing to research and the development of new technologies.
- Undertaking doctoral studies and/or advanced research in the field of Machine Learning and its impact on society
Learning outcomes
Access and admission
Access requirements
To be admitted to the official Master's Degree courses, students must hold an official university degree issued by a higher education institution in the European Higher Education Area or in other countries which entitles them to access Master's degree courses in the country issuing the degree.
In addition, in order to access this Master's degree a B2 English level certificate - or higher - must be submitted. The language level may also be proved by passing the corresponding test at Public University of Navarre’s Language Centre.
Specific criteria for the Master's degree
The Master’s degree Academic Commission is ultimately the entity in charge of deciding on admission.
In the case that the demand is higher than the offered positions, students will be accepted to this Master's degree according with the following scale:
- Academic record: 80 %
- Suitability of degree submitted: 20 %