PostGraduate in Marketing Intelligence
Education objectives
The Postgraduate Program in Marketing Intelligence aims to train experts and managers able to lead and guide the collection, compilation, analysis and dissemination of marketing information in organizations.
The goal of this program is to train technical staff and managers to:
- Develop strategies, methods and instruments of marketing management;
- Be aware of client behavior and create relationship policies;
- Master the processes and tools used for the storage, organization and access to information for marketing in organizations;
- Use the several methodologies and tools of exploration and analysis, in order to reduce the levels of uncertainty related to
solving marketing problems.
This Postgraduate Program gives access to the Master degree program in Data Driven Marketing, with a specialization in Marketing Intelligence (is offered in two formats: working hours and after working hours). For more information about this Master, please click here.
Applications - 4th 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 July 28th to August 17th, 2023. The selection process is based on the analysis of the applicant's academic and professional curriculum.
General characterization
DGES code
4956
Cicle
Postgraduate programmes
Degree
None
Access to other programs
This Postgraduate Program gives access to the Master Degree program in Data-Driven Marketing, with a specialization in Marketing Intelligence.
Coordinator
Paulo Miguel Rasquinho Ferreira Rita
Opening date
September 2023
Vacancies
Fees
€4.200
Schedule
After Working Hours
Teaching language
English
Degree pre-requisites
To earn the Postgraduate Program diploma in Marketing Intelligence, 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
To enter this program, applicants must meet the following requirements: hold a bachelor’s degree in a compatible field (completed by September 2023); be proficient in English (spoken and written).
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 |
200187 | Marketing Strategy and Innovation | 7.5 |
200197 | Brand Management | 3.5 |
200196 | Digital Marketing & E-Commerce | 7.5 |
Options | ||
200204 | Social Network Analysis | 3.5 |
200268 | Applied Network Analysis | 7.5 |
200012 | Business Intelligence I | 7.5 |
200201 | Data Science for Marketing | 7.5 |
200163 | Experimental Design | 4.0 |
200014 | Business Process Management | 7.5 |
200073 | Information Management Systems | 3.5 |
200189 | Descriptive Analytics in Marketing | 7.5 |
400082 | Digital Analytics | 7.5 |
200192 | Data Privacy, Security and Ethics | 4.0 |
200194 | Digital Transformation | 3.5 |
1º year - Spring semester | ||
---|---|---|
Code | Name | ECTS |
200170 | Consumer Behavior Insights | 7.5 |
200049 | Market Research | 7.5 |
200188 | Marketing Engineering and Analytics | 7.5 |
Options | ||
200203 | Machine Learning in Marketing | 7.5 |
200202 | Big Data for Marketing | 7.5 |
200013 | Business Intelligence II | 7.5 |
400019 | Customer Relationship Management Systems | 0.0 |
200071 | Knowledge Management | 3.5 |
400081 | Social Media Analytics | 7.5 |
200190 | Predictive Analytics in Marketing | 7.5 |
200200 | Search Engine Optimization | 4.0 |
200184 | Sampling Theory and Methods | 7.5 |
200298 | Data-driven decision making | 4.0 |