Masters in Business Analytics
Education objectives
The Master’s in Business Analytics aims at the development of solid technical, organizational, leadership, critical thinking and communication competencies for future managers and leaders of organizations (public or private, for-profit or not-for-profit) in a context increasingly dependent on algorithms and hybrid (human-machine) systems for decision making. It is therefore focused on the education of translators, i.e., people who understand organizations and the managerial problems they face and know how to use technology and leverage data to solve them.
General characterization
DGES code
37
Cicle
Master (2nd Cycle)
Degree
Master
Access to other programs
Available soon
Coordinator
Profª Rita Cunha
Opening date
Available soon
Vacancies
Available soon
Fees
Available soon
Schedule
Available soon
Teaching language
Available soon
Degree pre-requisites
With a collaboration with the Department of Computer Science of NOVA
School of Science and Technology, the program brings together the
technical and personal competencies of management with technology.
This
multidisciplinarity is key to attract applicant profiles with a first
cycle educational background in Sciences, Technology, Engineering or
Mathematics, but also Economics, Finance or Management.
Conditions of admittance
Available soon
Evaluation rules
Available soon
Structure
| Fall | ||
|---|---|---|
| Code | Name | ECTS |
| 67890 | Advanced Data Analysis | 3,5 |
| 67891 | Data Ecosystems and Governance in Organizations | 3,5 |
| 67892 | Advanced Programming for Data Science | 3,5 |
| 67893 | WEB and Cloud Computing | 3,5 |
| Spring | ||
|---|---|---|
| Code | Name | ECTS |
| 67890 | Advanced Data Analysis | 3,5 |
| 2487 | Machine Learning | 7 |
| 67891 | Data Ecosystems and Governance in Organizations | 3,5 |
| 67892 | Advanced Programming for Data Science | 3,5 |
| 67893 | WEB and Cloud Computing | 3,5 |
| Fall 1st Half | ||
|---|---|---|
| Code | Name | ECTS |
| 2489 | Data Curation | 3,5 |
| 2481 | Product Design and Development | 3,5 |
| 2480 | Digital Strategy and Transformation | 3,5 |
| 2269 | Empirical Methods for Finance | 3,5 |
| 2270 | Financial Modeling | 3,5 |
| Fall 2nd Half | ||
|---|---|---|
| Code | Name | ECTS |
| 2493 | Marketing Analytics | 3,5 |
| 2270 | Financial Modeling | 3,5 |
| 2491 | Data Visualization/Visualização de dados | 3,5 |
| Spring 1st Half | ||
|---|---|---|
| Code | Name | ECTS |
| 2467 | E-commerce | 3,5 |
| 2272 | Financial Econometrics | 3,5 |
| 2273 | Fintech Ventures | 3,5 |
| 2346 | Modeling Business Decisions | 3,5 |
| 2270 | Financial Modeling | 3,5 |
| Spring 2nd Half | ||
|---|---|---|
| Code | Name | ECTS |
| 2440 | Big Data Analysis | 3,5 |
| 2468 | Technology Strategy | 3,5 |
| 2397 | Innovation Management | 3,5 |
| 2465 | Open Innovation | 3,5 |
| 2441 | Digital Marketing | 3,5 |
| 2346 | Modeling Business Decisions | 3,5 |