Specialization in Digital Marketing and Analytics
Education objectives
The Master Program in Data Driven Marketing, with a specialization in Digital Marketing and Analytics, is aimed at managers, experts and other professionals who want to obtain skills in Digital Marketing and Web Analytics, using the most advanced methodologies for collecting, analyzing and processing data to support decision making in Web Marketing.
The goal of this program is to train technical staff and managers to:
- Understand the operating principles of Digital Marketing and Internet Social Media, as well the methodologies for its use in
creating value for business; - Understand and be able to apply analytical Social Media techniques;
- Understand the principles and metrics of Marketing in the Internet;
- Master the techniques of Search Engine Marketing, including AdWords campaign management and the development of
Search Engine Optimization (SEO) strategy.
This program is ranked as the best program in E-Business and Digital Marketing in Portugal and the 3rd in the Western Europe by Eduniversal, an international agency that publishes the annual ranking of the best MBA and Master programs in the world.
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
94352
Cicle
Specialization Area
Degree
Master
Access to other programs
This Master Degree gives acess to a Doctoral Program, confirm ours here.
Coordinator
Paulo Miguel Rasquinho Ferreira Rita
Opening date
September 2023
Vacancies
Fees
€6.000
Schedule
After working hours
Teaching language
English
Degree pre-requisites
The curricular component of the Study Plan (1st and 2nd semesters of the program) corresponds to 60 ECTS, 49 of which, are Mandatory Course Units. The remaining 11 ECTS correspond to Elective Course units.
This path is an option of
Master Degree in Data Driven Marketing
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); 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 |
| 200204 | Social Network Analysis | 3.5 |
| 200201 | Data Science for Marketing | 7.5 |
| 200163 | Experimental Design | 4.0 |
| 200187 | Marketing Strategy and Innovation | 7.5 |
| 200197 | Brand Management | 3.5 |
| 200196 | Digital Marketing & E-Commerce | 7.5 |
| 200189 | Descriptive Analytics in Marketing | 7.5 |
| 400082 | Digital Analytics | 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 |
| 200197 | Brand Management | 3.5 |
| 200014 | Business Process Management | 7.5 |
| 200073 | Information Management Systems | 3.5 |
| 200196 | Digital Marketing & E-Commerce | 7.5 |
| 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 |
| 200203 | Machine Learning in Marketing | 7.5 |
| 200202 | Big Data for Marketing | 7.5 |
| 200170 | Consumer Behavior Insights | 7.5 |
| 200049 | Market Research | 7.5 |
| 200188 | Marketing Engineering and Analytics | 7.5 |
| 400081 | Social Media Analytics | 7.5 |
| 200190 | Predictive Analytics in Marketing | 7.5 |
| 200200 | Search Engine Optimization | 4.0 |
| Options | ||
| 200203 | Machine Learning in Marketing | 7.5 |
| 200202 | Big Data for Marketing | 7.5 |
| 200013 | Business Intelligence II | 7.5 |
| 200170 | Consumer Behavior Insights | 7.5 |
| 400019 | Customer Relationship Management Systems | 0.0 |
| 200049 | Market Research | 7.5 |
| 200014 | Business Process Management | 7.5 |
| 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 |
| 2º year - Autumn semester | ||
|---|---|---|
| Code | Name | ECTS |
| 200265 | Dissertation/Internship Report/Project | 54.0 |
| 200086 | Research Methodologies | 6.0 |