- 1º ANO
1.º ANO
SEMESTRE
ECTS
HORAS Álgebra Linear / Linear Algebra
1.º Semestre
6
45 Design para Interfaces I / Design for Interfaces I
1.º Semestre
6
60 Fundamentos de Programação / Fundamentals of Programming
1.º Semestre
6
60 Matemática I / Mathematics
1.º Semestre
6
60 Teoria e Optimização de Grafos para Ciência de Dados / Graph Theory and Optimization for Data Science
1.º Semestre
6
60 Análise Exploratória de Dados / Exploratory Data Analysis
2.º Semestre
6
60 Bases de Dados / Databases
2.º Semestre
6
45 Design para Interfaces II / Design for Interfaces II
2.º Semestre
6
60 Estruturas de Dados e Conhecimento / Data Structures and Knowledge
2.º Semestre
6
60 Matemática II / Mathematics II
2.º Semestre
6
60 - 2º ANO
2.º ANO
SEMESTRE
ECTS
HORAS
Análise e Processamento de Big Data / Big Data Analysis and Processing
1.º Semestre
6
60
Inteligência Artificial / Artificial Intelligence
1.º Semestre
6
60
Laboratórios de Estatística e Modelação Linear Aplicada à Ciência dos Dados / Statistics and Linear Modeling Labs Applied to Data Science
1.º Semestre
6
60
Programação e Análise de Dados / Data Programming and Analysis
1.º Semestre
6
60
Visualização Interativa de Dados / Interactive Data Visualization
1.º Semestre
6
60 Aprendizagem Máquina Supervisionada e não Supervisionada / Supervised and Unsupervised Machine Learning
2.º Semestre
6
75 Design de Informação - Infografia I / Information Design - Infographics
2.º Semestre
6
60 Engenharia de Software / Software Engineering
2.º Semestre
6
60
Inovação By Design / Innovation By Design
2.º Semestre
6
45
Programação Estruturada / Structured Programming
2.º Semestre
6
45
- 3º ANO
3.º ANO
SEMESTRE
ECTS
HORAS
Design de Informação – Infografia II / Information Design - Infographics II
1.º Semestre
6
60
Ética dos Dados / Data Ethics
1.º Semestre
3
30
Métodos de Investigação para Ciência de Dados / Research Methods for Data Science
1.º Semestre
5
45
Processamento de Texto e Linguagem Natural / Text Processing and Natural Language
1.º Semestre
6
60
Projeto de Ciência de Dados / Data Science Project
1.º Semestre
10
30 Ciência de Dados Aplicada à Internet das Coisas / Data Science Applied to the Internet of Things
2.º Semestre
6
60 Opcional I / Elective I
Análise e Gestão do Comportamento do Consumidor / Consumer Behavior Analysis and Management
Decision Science
Gestão de Dados / Data Management
Gestão e Empreendedorismo / Management and Entrepreneurship
Liderança de Equipas Virtuais / Virtual Team Leadership
Negócios Digitais / Digital Business2.º Semestre
3
30 Opcional II / Elective II
Análise e Gestão do Comportamento do Consumidor / Consumer Behavior Analysis and Management
Decision Science
Gestão de Dados / Data Management
Gestão e Empreendedorismo / Management and Entrepreneurship
Liderança de Equipas Virtuais / Virtual Team Leadership
Negócios Digitais / Digital Business2.º Semestre
3
30
Projeto de Visualização de Dados / Data Visualization Project
2.º Semestre
10
30
Segurança, Direito e Privacidade no Ciberespaço / Cybersecurity, Law, and Privacy
2.º Semestre
5
45
Sistemas de Suporte à Decisão Baseada em Dados / Data-Driven Decision Support Systems
2.º Semestre
3
30
Approved Registry number at Ministry: R/A-Cr 28/2023.
Accredited Course by the Agency for Assessment and Accreditation of Higher Education.
Bachelor’s Degree lectured in association with ISTEC - Instituto Superior de Tecnologia Avançadas de Lisboa.
COORDINATION
 |
 |
Doctor Sandra Gama (PhD)
|
Specialist Mário Carvalho
|
Online Application Information Request
The Bachelor's Degree in Data Science and Visualization provides a solid training in the fundamental areas of data science and visualization, preparing students for various related careers. Throughout the course, students will develop the following skills:
Data Science:
- Mastery of data science concepts and techniques;
- Skills in statistical analysis and predictive modeling;
- Knowledge of machine learning algorithms and artificial intelligence;
- Ability to apply data science methodologies to real-world problems.
Data Visualization:
- Mastery of data visualization principles, techniques, and tools;
- Fundamentals of design applied to visualization;
- Skills in interactive data visualization and exploration;
- Knowledge of visual design and communication principles;
- Ability to create informative and impactful visualizations.
Software and Project Management:
- Fundamentals of Programming applied to Data Science;
- Fundamentals of Databases;
- Skills in data science and visualization project management;
- Capabilities in project planning, coordination, and execution;
- Knowledge of agile methodologies and best project management practices.
Ethics and Data Security:
- Understanding of ethical and legal aspects of data science;
- Knowledge of data protection and privacy;
- Identification and mitigation of security risks;
- Knowledge of regulations and security standards in data science.
SPECIFIC OBJECTIVES
Based on the topics covered throughout the study cycle, the objectives of the Data Science and Visualization course include empowering students to develop critical thinking in the different fundamental areas of the course. In the area of Data Science, the goal is to enable students in data collection, processing, and analysis techniques, applying critical thinking to solve problems and make informed decisions. In the area of Data Visualization, the focus is on empowering students to create clear and effective visual representations of data, aiming to communicate complex information in an understandable and impactful way, allowing the creation of Information Visualizations that enable efficient and effective task execution, relieving the cognitive load associated with data interpretation. Additionally, the course aims to develop software engineering, artificial intelligence, project management, ethics, and data security capabilities, preparing students to deal with diverse challenges in the field of data science and visualization. These skills will provide students with the necessary tools to act as competent and ethical professionals in an ever-evolving field like Data Science and Visualization.
TARGET AUDIENCE
The Bachelor's Degree in Data Science and Visualization is intended for the entire society, including students who have completed secondary education, individuals over 23 years old, graduates of professional technical higher education courses, and other bachelor's degree holders who may benefit from advanced knowledge in the visualization and data science field. It is also open to professionals in the area who wish to specialize in their respective fields of training.
MAIN CAREER OPPORTUNITIES
Data Science:
- Data Scientist.
- Data Analyst.
- Machine Learning Specialist.
- Business Intelligence Analyst.
Data Visualization:
- Data Visualization Designer.
- Information Design Specialist.
- Data Visualization Analyst.
- Interactive Visualizations Programmer.
- Data Visualization Consultant.
- Data Visualization Project Manager.
Project Management:
- Data Science.
- Project Manager.
- Visualization Project Team Leader.
- Technology Project Management Consultant.
- Data Business Analyst.
- Analytics Program Manager.
Ethics and Data Security:
- Ethics and Data Privacy Specialist.
- Data Security Analyst.
- Data Compliance Manager.
- Artificial Intelligence Ethics Consultant.
PARTNER ENTITIES
Ivity; Cofina; Codedesign; Fuel
CONFERRED QUALIFICATION TITLE
Bachelor Graduate in Data Science and Visualization
STUDY TIME SCHEME:
Day-time and Evening Classes
STUDY PLAN:
TOTAL PROGRAMME DURATION
6 semesters (3 years).
EQUIPMENT AND DIDACTIC MATERIALS
Several computer labs equipped with Apple iMac 21" and HP All-in-one 24" for Multimedia.
The equipment is equipped with various software [Adobe and Office] dedicated to content editing and management (text, image).
