Accreditations
This undergraduate degree trains competent professionals who understand how and which data should be collected, organized and managed, and enables them to integrate and quickly process large volumes and wide varieties of data (Big Data). By developing their computational and mathematical reasoning, which are fundamental for Data Mining, Machine Learning and Intelligent Agents, this degree endows its graduates with strong analytical, creative and ethical skills, which translate into the ability to extract, build and analyse knowledge, and communicate it in a sustained manner, either for decision-making or the creation of new products and services.
Through the continuous and systematic use of individual and group work, the practical component is reinforced by putting students in contact with real data and challenges, proposed by a variety of guests from financial and technological companies, public administration, and bodies related to health, human and social sciences. These activities end up connecting the students to the research and innovation aspects of the course.
Once the course is finished, graduates will have at their disposal a wide range of employment opportunities and a very high rate of employability.
This degree is intended for all young people looking for a suitable training that will enable them to implement and manage analytical processes in organizations and decision support systems. In particular, to all those who enjoy interesting challenges and feel the need to actively intervene in the construction of their (and our) future.
If the student wishes to pursue further studies, the curriculum of the degree in Data Science has been created with the premise of developing extended training that can be coordinated with a 2nd cycle of studies in areas such as Applied Mathematics, Artificial Intelligence, Computer Science and Information. Graduates are able to continue with the Master in Data Science or complementing their studies with other courses, such as the Master in Integrated Decision Support Systems (MSIAD), the Master in Business Analytics (MAG), or the Master in Informatics Engineering (MEI). The latter holds the EUR-ACE Quality Mark, awarded by the European Network for Accreditation of Engineering Education (ENAEE).
In Portugal, the International Student Statute grants foreign students (from outside of the European Union) a specific number of places and access conditions. This Statute makes it possible to apply directly to certain degree courses at Iscte.
For more information, click here.
Director(s) message
The need for companies to obtain value from data, to organize and interpret it, along with the challenges arising from it, were the drivers for the emergence of the Data Science area.
Today, all organizations generate and use data, not only as a decision support tool, but also to develop new products and services. Over the past decade, there has been a veritable explosion in the amount of data being collected. But how can we use and build knowledge from these pieces of information?
The new digital challenges, both in industry and in research, have led to a pressing need to provide adequate multidisciplinary training to develop mathematical, statistical and computational reasoning skills, aimed at pattern recognition and construction of predictive models, as well as their analysis, interpretation and anticipation.
Internationally recognized as a multidisciplinary area, Data Science is an emerging field, responding to the current challenges created by the large-scale digital proliferation of data and converging skills in Mathematics, Statistics, Computer Science and Information Technology.
General information