The Portuguese Catholic University (UCP), in partnership with the University of Saint Joseph (USJ) in Macau, is launching this Bachelor’s Programme in Data Science and Technology (DST), which will be delivered in online distance learning (e-learning). This new cycle of studies is motivated by its pioneering nature, not only because of the emerging and rapidly growing area of data science and its applications but, above all, because of how it is taught.

The cycle of studies is focused on Data Science and Technology, an area of remarkable growth that demands qualified professionals in a highly computerised, interconnected, and knowledge-dependent society that relies heavily on large volumes of information. This pedagogical offer will prepare students for the “professions of the future.”

Those who attend or will attend higher education today are regular users of web resources and are, therefore, increasingly appropriating new technologies as an extension of the human condition. This is why online distance learning should be seen as an alternative to the face-to-face modality while offering students high levels of flexibility for organising their study from wherever they are located without the need to visit a physical campus but a virtual space. 

All content and interaction mechanisms are available online, and asynchronous online communication is favored. This is complemented by synchronous online communication (videoconferencing-based) in all learning units.

The teaching-learning process is in distance learning in virtual classrooms using a specialised e-learning platform and adopting the virtual pedagogical model of the Portuguese Open University.

This cycle of studies will allow those with work-related restrictions the flexibility of time and space to adapt to each student's needs.

Students are only required to have access to a computer with a broadband internet connection, English proficiency and high motivation to interact online and learn!

This cycle of studies is entirely taught in English.
 

General Objectives

The cycle of studies aims to train professionals with a high civic and ethical sense, providing solid theoretical foundations and technological skills combined with knowledge of how organizations work, meeting the need for constant innovation in the fields of data collection, integration, manipulation and processing, as well as the effective and ethically responsible provision of information.

Graduates are expected to be able to:

1. Lead and manage organizational intervention projects aimed at adopting and making good use of data science and technology (DST) solutions;
    
2. Design and integrate DST technological solutions considering the broadest areas of organizational intervention involving scalability, optimization, analysis, processing and manipulation of large volumes of data;
    
3. Design and develop artefacts in the form of applications or systems that encapsulate DST solutions for the most diverse organizational contexts.
    

Learning Objectives

The study cycle comprises the following learning objectives:

1. To provide grounded and problematizing knowledge of models, theories, conceptual frameworks and technologies in the areas of mathematics, statistics, computer science and information systems that frame the development and integration of innovative data science and technology solutions in organizations;
    
2. To enable autonomous professional performance in organizations of a diverse nature, through the development of intelligent systems capable of collecting, processing, storing, visualizing and extracting knowledge from large amounts of data in a technologically efficient manner;
    
3. Training for the development, interpretation and ethically responsible evaluation of state-of-the-art machine learning and artificial intelligence methodologies applied in real contexts;
    
4. Qualify to exercise technological supervision in development projects in the context of data science and technology.

Career Prospects

• Big Data Analyst
• Data Scientist
• Data Engineer
• Machine Learning Specialist
• Machine Learning Algorithm Development Specialist
• Artificial Intelligence Systems Specialist

Those careers can be executed in diverse sectors of activity.

Accreditation
 

A3ES
Process NCE/24/2400255 accessed on 2025-04-02