Specialization in Business Analytics
Education objectives
The popularity of Data Science and Analytics has been steadily growing in the last few years, both in Industry and Academia. The Master degree Program in Data Science and Advanced Analytics, with a specialization in Business Analytics, is aimed at market oriented people, who want to apply effective analytical models to different business problems, interpreting the results and their implications to the business, with the objective of taking data driven decisions to optimize the business process.
The best students of the 1st year of the Master in Data Science and Advanced Analytics will be invited for a 6 month paid internship, to be held during the 2nd year, in one of the following institutions: Accenture, BI4ALL, Feedzai, Future Healthcare, Grupo Ageas Portugal, iFood, Izertis, Millennium BCP, NOVA IMS, SAS and Tranquilidade.
This Program will provide a set of interdisciplinary skills and tools such as:
- Understanding of the main paradigms associated with large databases and data warehouses;
- Understanding the processes of decision making;
- Mastering data mining tools, in particular for "Big Data" related problems;
- Mastering the processes of creation and maintenance of descriptive and predictive models;
- Recognizing and applying the most effective analytical models to different business cases;
- Interpreting models and their implications to the business.
Applications - 3rd call
To complete the application, the applicant must register in NOVA IMS' Applications Portal, fill the form, upload their Curriculum Vitae, pay the application fee (€ 51), and submit the application in the end from June 21st until July 21st, 2022. The selection process is based on the analysis of the applicant's academic and professional curriculum.
General characterization
DGES code
75121
Cicle
Specialization Area
Degree
Master
Access to other programs
Coordinator
Roberto Henriques
Opening date
September 2022
Vacancies
Fees
€6.200
Schedule
Working Hours
Teaching language
English
Degree pre-requisites
This path is an option of
Master in Data Science and Advanced Analytics
Conditions of admittance
The requirements for the applications are: a degree in a compatible field (complete until September); analysis of the applicants' academic and professional curriculum.
Evaluation rules
Structure
1º year - Autumn semester | ||
---|---|---|
Code | Name | ECTS |
200179 | Machine Learning | 7.5 |
200174 | Storing and Retrieving Data | 4.0 |
200175 | Data Mining | 7.5 |
200178 | Statistics for Data Science | 7.5 |
200211 | Programming for Data Science | 3.5 |
1º year - Spring semester | ||
---|---|---|
Code | Name | ECTS |
200180 | Deep Learning | 3.5 |
200282 | Biga Data Analytics | 7.5 |
200011 | Business Intelligence | 7.5 |
200208 | Business Cases with Data Science | 7.5 |
200278 | Business Process Management | 3.5 |
200142 | Computational Intelligence for Optimization | 7.5 |
200181 | Text Mining | 4.0 |
200283 | Digital Transformation | 4.0 |
Options | ||
200180 | Deep Learning | 3.5 |
200292 | Ethics in Data Science | 3.5 |
200142 | Computational Intelligence for Optimization | 7.5 |
200207 | Big Data Modelling and Management | 3.5 |
200294 | Neural and Evolutionary Learning | 4.0 |
200293 | Machine Learning Operations | 3.5 |
200295 | Reinforcement Learning | 4.0 |
200181 | Text Mining | 4.0 |
200176 | Data Visualization | 4.0 |
2º year - Autumn semester | ||
---|---|---|
Code | Name | ECTS |
200290 | Dissertation/ Work Project/ Interneship Report | 54.0 |
200289 | Research Methods | 6.0 |
200289 | Research Methods | 6.0 |