PostGraduate in Data Science for Marketing
Education objectives
The Postgraduate program in Data Science for Marketing aims to fill a gap in the postgraduate training of marketing professionals who need to gain new skills to be able to actively participate in the development and application of analytical marketing models. With the proposed study plan, this Post-graduation presents an up-to-date structure that combines several areas of marketing with a transversal approach of data science to leverage them.
This program is designed to provide excellent training, articulating key concepts and challenges for marketing decision-making in its multiple strategic, innovation and methodological strands with practical data-oriented processing (data science & big data), artificial intelligence (machine learning) and analysis of social networks of consumers. The versatility in the offer of optional curricular units also allows to reinforce theoretical and practical knowledge in several related areas such as digital marketing, social media, e-commerce and search engine optimization.
Applications - 5th 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 June 18th and July 18th, 2024. The selection process is based on the analysis of the applicant's academic and professional curriculum.
General characterization
DGES code
E245
Cicle
Postgraduate programmes
Degree
None
Access to other programs
This Program gives access to the Master Degree in Data-Driven Marketing, with a specialization in Data Science for Marketing
Coordinator
Paulo Miguel Rasquinho Ferreira Rita
Opening date
September 2024
Vacancies
Fees
€4.200
Schedule
After Working Hours
Teaching language
English
Degree pre-requisites
To earn the postgraduate program diploma in Data Science for Marketing, students complete a total of 60 ECTS, of which 41 are mandatory and the remaining 19 ECTS will be chosen by the students from a wide range of available course units.
Conditions of admittance
The requirements for the applications are: a degree in a compatible field (complete until September 2024); analysis of the applicants' academic and professional curriculum.
Evaluation rules
The assessment method will be continuous assessment, i.e. through individual or group work, projects, quizzes, tests/exams, etc.
At the beginning of each academic year, it is up to each teacher of each Curricular Unit (CU) to define how assessment will be carried out in their CUs, and this information is then made available via the student platform.
Structure
| 1º year - Autumn semester | ||
|---|---|---|
| Code | Name | ECTS |
| 200204 | Social Network Analysis | 3.5 |
| 200201 | Data Science for Marketing | 7.5 |
| 200187 | Marketing Strategy and Innovation | 7.5 |
| Options | ||
| 200268 | Applied Network Analysis | 7.5 |
| 200012 | Business Intelligence I | 7.5 |
| 200163 | Experimental Design | 4.0 |
| 200195 | Information Systems Development | 4.0 |
| 400020 | Information Systems Governance | 3.5 |
| 200197 | Brand Management | 3.5 |
| 200014 | Business Process Management | 7.5 |
| 200070 | Information Technologies Services Management | 4.0 |
| 200073 | Information Management Systems | 3.5 |
| 200193 | Data Management and Storage | 4.0 |
| 200196 | Digital Marketing & E-Commerce | 7.5 |
| 200189 | Descriptive Analytics in Marketing | 7.5 |
| 400082 | Digital Analytics | 7.5 |
| 200291 | Descriptive Methods of Data Mining | 7.5 |
| 200165 | Descriptive Methods of Data Mining | 7.5 |
| 200192 | Data Privacy, Security and Ethics | 4.0 |
| 200194 | Digital Transformation | 3.5 |