The main objective is to provide the graduate with skills, based on computational tools, to know how to extract and analyze the essential knowledge of a large volume of data (Big Data), structured or not, giving a sustained voice to this information, and to know how to use this knowledge efficiently according to the objectives set, either in support of decision making or in the production of new products and services. It is intended to combine this competence with knowing how to develop Artificial Intelligence (AI) ecosystems, in particular Machine Learning, allowing the analysis of this large set of data.
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|---|---|---|
| conditions | array | Array(3) |
| >ProvasEspecificasCurso.curso | string | '2614' |
| >ProvasEspecificasCurso.ano_lectivo | integer | 2025 |
| >ProvasEspecificasCurso.aplicavel_cna | boolean | true |
| test_server | boolean | false |
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| 0 | array | Array(3) |
| >ProvasEspecificasCurso | array | Array(9) |
| >TipoProvasEspecificasCurso | array | Array(4) |
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| >TipoProvasEspecificasCurso | array | Array(4) |
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| >ProvasEspecificasCurso | array | Array(9) |
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| >ProvasEspecificasGrupo | array | Array(4) |
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| >ProvasEspecificasCurso | array | Array(9) |
| >TipoProvasEspecificasCurso | array | Array(4) |
| >ProvasEspecificasGrupo | array | Array(4) |
| 4 | array | Array(3) |
| >ProvasEspecificasCurso | array | Array(9) |
| >TipoProvasEspecificasCurso | array | Array(4) |
| >ProvasEspecificasGrupo | array | Array(4) |
| 5 | array | Array(3) |
| >ProvasEspecificasCurso | array | Array(9) |
| >TipoProvasEspecificasCurso | array | Array(4) |
| >ProvasEspecificasGrupo | array | Array(4) |
Artificial Intelligence and Data Science
Bachelor's Degree
Ano Letivo 2025/2026
Course Overview
The Degree in Artificial Intelligence and Data Science is a bachelor's degree designed to promote students' ability to face the current challenges of the digital age. Combining foundational knowledge of Computer Science with a solid formation in Mathematics / Statistics, students acquire an understanding of the core of Artificial Intelligence with an emphasis on Machine Learning, data analysis, statistics, Big Data and high performance computing, among others.
The main objective is to provide the graduate with skills, based on computational tools, to know how to extract and analyze the essential knowledge of a large volume of data (Big Data), structured or not, giving a sustained voice to this information, and to know how to use this knowledge efficiently according to the objectives set, either in support of decision making or in the production of new products and services. It is intended to combine this competence with knowing how to develop Artificial Intelligence (AI) ecosystems, in particular Machine Learning, allowing the analysis of this large set of data.
The main objective is to provide the graduate with skills, based on computational tools, to know how to extract and analyze the essential knowledge of a large volume of data (Big Data), structured or not, giving a sustained voice to this information, and to know how to use this knowledge efficiently according to the objectives set, either in support of decision making or in the production of new products and services. It is intended to combine this competence with knowing how to develop Artificial Intelligence (AI) ecosystems, in particular Machine Learning, allowing the analysis of this large set of data.
Organic Unit:
School of Science and Technology
DGES Code:
0602/L227
Duration:
6 Semesters/180 ECTS credits (168 required and 12 optional in curricular units)
Language:
Portuguese
Regime:
Presencial
CNAEF Areas:
- Computer science (481)
Career Prospects
O curso forma profissionais aptos para trabalharem enquanto analistas e/ou cientista de dados, especialistas em IA, em empresas e laboratórios de investigação, entre outros, e em entidades públicas ou privadas (por exemplo, empresas tecnológicas, telecomunicações, têxtil, calçado, automóvel, administração pública, bancos, seguradoras, ciências da vida e da saúde, entre outras).
Entry Requirements
Entrance Exams
One of the following sets:
- 02 - Biology and Geology (25%)
- 19 - Mathematics A (25%)
- 04 - Economy (25%)
- 19 - Mathematics A (25%)
- 07 - Physics and Chemistry (25%)
- 19 - Mathematics A (25%)
- 18 - Portuguese (25%)
- 19 - Mathematics A (25%)
- 09 - Geography (25%)
- 19 - Mathematics A (25%)
- 10 - Descriptive Geometry (25%)
- 19 - Mathematics A (25%)
Formula for calculating the applications of the General Access System (CNA):
50% Média de secundário | 50% Provas de ingresso
50% Média de secundário | 50% Provas de ingresso
Minimum Classifications:
Application classification: 100 points
Entrance exams: 95 points
Application classification: 100 points
Entrance exams: 95 points
Last admission grade 2024/2025: 115.0
Access Routes and Applications
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '25' |
| fase2 | string | '18' |
| fase3 | string | '5' |
National Access Route to Higher Education (CNA)
Places available 1st phase: 25
Places available 2nd phase: 18
Places available 3rd phase: 5
Places available 2nd phase: 18
Places available 3rd phase: 5
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '1' |
| fase2 | string | '0' |
| fase3 | NULL |
International Students
Places available 1st phase: 1
Places available 2nd phase: 0
Places available 2nd phase: 0
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '1' |
| fase2 | NULL | |
| fase3 | NULL |
Over 23 Years of Age
Places available 1st phase: 1
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '1' |
| fase2 | NULL | |
| fase3 | NULL |
Degree Holders
Places available 1st phase: 1
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '0' |
| fase2 | NULL | |
| fase3 | NULL |
CET Holders
Places available 1st phase: nd
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '0' |
| fase2 | NULL | |
| fase3 | NULL |
TeSP Holders
Places available 1st phase: nd
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '0' |
| fase2 | NULL | |
| fase3 | NULL |
Special Regimes
Places available 1st phase: nd
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '2' |
| fase2 | NULL | |
| fase3 | NULL |
Change of Institution/Course Pair
Places available for first year 1st phase: 2
Places for subsequent years: not subject to places
Places for subsequent years: not subject to places
| Attribute | Type | Value |
|---|---|---|
| fase1 | string | '0' |
| fase2 | NULL | |
| fase3 | NULL |
Holders of Professional Course Diploma
Places available 1st phase: nd
Readmission
Places available: not subject to places
Tuition Fees
Annual Tuition Fees
Students from EU countries
697.00 €
International Students
2500.00 €
International Students with Merit Scholarships
1050.00 €
International Students with Cooperation and Development Grants
1250.00 €
Do you know what support, scholarships, and awards you can access while attending your course?
Find out more here and apply.
Course Committee
Do you want an academic experience in another national or international higher education institution?
Get to know the programs, the partner institutions where you can do a period of mobility.
Timetables
Academic Year: 2025/2026
Documents
| Attribute | Type | Value |
|---|---|---|
| id | string | '2614' |
| sigla | string | 'B_L_CDIA' |
| codigo | string | '746' |
| nome | string | 'Inteligência Artificial e Ciência de Dados' |
| grau | string | 'lic' |
| tipo | string | 'bolonha' |
| estado | string | 'valido' |
| ano_lectivo | string | '2023' |
| plano | string | '1110727' |
| area_cientifica | NULL | |
| registo_dges | string | 'R/A-Cr 23/2023' |
| edicao | boolean | false |
| created | string | '04/08/2021' |
| modified | string | '15/01/2025' |
| regime_frequencia | string | 'd' |
| escola | string | '31031' |
| modified_by | string | 'mdac' |
| created_by | string | 'mdac' |
| semestre_inicio | string | '1' |
| erasmus | NULL | |
| area_formacao | NULL | |
| codigo_siag | string | '950106201' |
| nome_abbrev | string | 'LIC_CIEDADINTART' |
| observacoes_prr | string | 'Despacho 135/2023' |
| prr | string | 'prometheus' |
| deslocalizado | boolean | false |
| curso_instrumentos_musica | boolean | false |
| curso_ensino_provas_pt | boolean | false |
| impulso | string | 'jovens' |
| regime_lecionacao | string | 'presencial' |
| num_gd | string | '20915/2021 _ GD/37578/2022/P1' |
| subtipo_curso_formacao | NULL | |
| link_registo_dges | string | 'https://www.dges.gov.pt/simges/public/www/cursos/10857' |
| nome_abrev | string | 'Inteligência Artificial e Ciência de Dados' |
| app_moveis | string | 'Inteligência Artificial e Ciência de Dados (cód. 746)' |
| nome_cod | string | 'Inteligência Artificial e Ciência de Dados (cód. 746)' |
| Attribute | Type | Value |
|---|---|---|
| id | string | '26' |
| curso | string | '2614' |
| ano_lectivo | string | '2025' |
| programa_financiamento | string | 'prometheus' |
| programa_financiamento_obs | string | 'Despacho 135/2023' |
| impulso_prr | string | 'jovens' |
| created | string | '24/09/2025' |
| modified | string | '24/09/2025' |
| created_by | string | 'siiue2' |
| modified_by | string | 'siiue2' |
| ProgramasFinanciamento | array | Array(6) |
| >id | string | 'prometheus' |
| >nome | string | 'Prometheus' |
| >created | string | '23/01/2023' |
| >modified | string | '23/01/2023' |
| >created_by | string | 'ljcq' |
| >modified_by | string | 'ljcq' |
Regulation
Contact Information
Director:
Pedro Salgueiro [pds@uevora.pt]
Academic Manager: Raquel Maria Pitadas de Matos
Academic Services (online): SAC.ONLINE
Accreditations and Certifications
