Bachelor Degree

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Accredited
6 Years
27 Mar 2025
Accreditation DGES
Initial registry R/A-Cr 27/2019 de 14-06-2019
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Contacts
School of Technology and Architecture
Secreatariat
Sedas Nunes Building (Building I), room 1E07
secretariado.ista @iscte.pt
(+351) 210 464 013
9:30 - 18:00
Iscte Business School
Secretariat
Ala Autónoma, Office 235
ibs@iscte-iul.pt
(+351) 210 464 014

Tuition fee EU nationals (2025/2026)

1.stYear 697.00 €
2.thYear 697.00 €
3.thYear 697.00 €
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Lectured in Portuguese
Teaching Type In person

The undergraduate degree in Data Science is based on the convergence of different scientific areas - Mathematics, Statistics and Informatics – and its programme structure is structured around projects which foster both practical and theoretical thinking, with a view towards granting the student an informed, critical, and autonomous understanding of data in the face of the various dimensions of the Knowledge Society and the Digital Revolution.

The Bachelor's is well-situated for helping students to comprehend and explore the areas of this knowledge-base. These actions support the student's progressive acquisition of independence and the capacity to respond to problems of increasing complexity.

With the synthesis, which occurs in the last two semesters, the coherence of the training program is consolidated around responsible practice and the exceptional professional skills required in order to respond to the challenges of modern society.

Programme Structure for 2025/2026

1st Year
Probabilities and Sampling
6.0 ECTS
Calculus Topics II
6.0 ECTS
Data in Science, Bussiness and Society
6.0 ECTS
Exploratory Data Analysis
6.0 ECTS
Optimization for Data Science
6.0 ECTS
Calculus Topics I
6.0 ECTS
Linear Algebra Fundamentals
6.0 ECTS
Programming
6.0 ECTS
Data Structures and Algorithms
6.0 ECTS
Critical Thinking
2.0 ECTS
Writing Scientific and Technical Texts
2.0 ECTS
2nd Year
Security, Ethics and Privacy
6.0 ECTS
Network Analysis
6.0 ECTS
Unsupervised Learning Methods
6.0 ECTS
Supervised Learning Methods
6.0 ECTS
Big Data Processing
6.0 ECTS
Fundamentals of Database Management
6.0 ECTS
Heuristic Optimization
6.0 ECTS
Big Data Storage
6.0 ECTS
Computational Statistics
6.0 ECTS
Regression Models
6.0 ECTS
3rd Year
Applied Final Project in Data Science
12.0 ECTS
Web Interfaces for Data Management
6.0 ECTS
Stocastic Modelling
6.0 ECTS
Symbolic Artificial Intelligence for Data Science
6.0 ECTS
Applied Project in Data Science II
6.0 ECTS
Longitudinal Models
6.0 ECTS
Introduction to Deep Learning
6.0 ECTS

Objectives

The Bachelor's Degree in Data Science aims to train professionals capable of handling the growing amount of data generated by modern society. This degree aims at acquiring analytical skills and applying appropriate methodologies to the data cycle.

In this course, skills are developed in Computer Science and Programming Technologies, for the development of basic software tools for Data Science; Information Systems, for designing and managing Databases, storing and processing large volumes of data (Big Data); Artificial Intelligence; Statistics and Data Analysis, to analyze and classify data, identify patterns, make forecasts and simulations. Additionally, students are promoted and made aware of the importance of Security, Ethics, and Privacy.

Many course units include group courseworks, which require and promote teamwork. In addition to theoretical-practical classes, many course units have practical-laboratory classes, in which the methodologies and technologies relevant to Data Science are applied.

The degree also includes applied project course units, in which student groups apply the studied contents to real data and problems. In the “Final Applied Project in Data Science”, each group of students develops a project proposed by an external entity.


The bachelor should be able to attain the learning outcomes:


Skills:

  • be able to collect, clean, transform, an query data;
  • be able to organize, summarise, visualize data and outcomes;
  • be able to select and apply the appropriate methodologies to perform data analysis, statistical inference, and predictive and prescriptive analysis;
  • be able to implement algorithms in a general purpose language;
  • be able to evaluate and reflect on the level of security, data protection and privacy of a specific technological solutions.


Competencies:

  • be able to develop data-driven analysis;
  • be able to search and evaluate scientific knowledge;
  • be able to work within multidisciplinary teams, while communicating results to stakeholders.

Contacts
School of Technology and Architecture
Secreatariat
Sedas Nunes Building (Building I), room 1E07
secretariado.ista @iscte.pt
(+351) 210 464 013
9:30 - 18:00
Iscte Business School
Secretariat
Ala Autónoma, Office 235
ibs@iscte-iul.pt
(+351) 210 464 014
Apply