Bachelor in Data Science for Management

Course Objectives

Data science is becoming increasingly important to society and business as a strategic tool for making better decisions. This study cycle is highly technical and focuses on developing the quantitative and methodological skills needed to utilize the potential of data science. The plan is designed to provide students with substantial hands-on competence in data science and the ability to use it to
create value for organizations in a wide range of areas such as management, marketing, finance and economics.

Access Conditions

The information provided does not exempt the consultation to the page of the General Directorate of Higher Education (DGES)

Professional Outlets

Data Analyst
Big Data Specialists
Business Intelligence Specialist
AI and Machine Learning Specialists
Data Scientist
FinTech Expert

To know more statistical information about this course click here.

Learning Language

Portuguese Language.

Learning Objectives

Know the central role of data in an organizations value creation strategy;
Understand how data-driven thinking is structured and streamlined;
Know the main concepts and techniques of data science;
Acquire programming skills in Python and other machine learning tools to extract, organize and analyze data from various sources;
Knowing how to explore data sets of different dimensions, incorporating the quantification of uncertainty in the analysis and prediction of future results, making it possible to evaluate the impact of possible decisions;
Learn to extract, transform, load and visualize data and analysis;
Understand the main phases of a data science project, being able to apply them in practical implementations;
Gain knowledge in management support, from accounting, business management, fundamental economics and finance.

Access to Superior Studies

The graduate degree allows the students to apply for Post-graduate.

Course Coordinators

Common Field

Curricular Year: 1
Curricular Unit Code ECTS Period
Data Analytics 51001826 4 1st S
Financial Accounting for Management 51001764 6 1st S
Macroeconomic Analysis 51001770 4 1st S
Mathematical Analysis I 51001792 6 1st S
Programming 51001815 10 1st S
Applied statistics 51001747 4 2nd S
Data Science Topics 51001736 11 2nd S
Introduction to Management 51001753 4 2nd S
Mathematical Analysis II 51001809 6 2nd S
Microeconomics 51001781 5 2nd S

Curricular Year: 2
Curricular Unit Code ECTS Period
Artificial Intelligence 51001874 6 1st S
Databases 51001852 6 1st S
Management Accounting 51001880 6 1st S
Operations Research 51001891 6 1st S
Programming for Data Science 51001905 6 1st S
Corporate Finance 51001916 5 2nd S
Extraction, Transformation, Loading and Visualization 51001848 9 2nd S
Marketing 51001863 4 2nd S
Multivariate Analysis 51001927 8 2nd S
Strategic Management 51001837 4 2nd S

Curricular Year: 3
Curricular Unit Code ECTS Period
Development for the WEB 51001951 4 1st S
Financial and Operational Reporting 51002013 6 1st S
Machine Learning 51001990 9 1st S
Organization Behavior 51001962 5 1st S
Time Series 51001973 6 1st S
Computer Law 51001938 4 2nd S
FinTech – Financial Technology 51002002 6 2nd S
Project in Data Science 51001949 15 2nd S
Web Marketing and E-Commerce 51001984 5 2nd S