Especialização em Data Science for Marketing

Education objectives

The Master Program in Data Driven Marketing, with a specialization 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 - 2nd call for applications
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 April 7th to May 13th, 2021. The selection process is based on the analysis of the applicant's academic and professional curriculum.

General characterization

DGES code

94353

Cicle

Specialization Area

Degree

Master

Access to other programs

Coordinator

Paulo Miguel Rasquinho Ferreira Rita

Opening date

September 2021

Vacancies

Fees

€6.000

Schedule

After working hours

Teaching language

English

Degree pre-requisites

This path is an option of

Mestrado em 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 2021); be proficient in English (spoken and written).

Evaluation rules

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
400082 Digital Analytics 7.5
200187 Marketing Strategy and Innovation 7.5
200197 Brand Management 3.5
200196 Digital Marketing & E-Commerce 7.5
200189 Descriptive Analytics in Marketing 0.0
Options
200204 Social Network Analysis 3.5
200012 Business Intelligence I 7.5
200201 Data Science for Marketing 7.5
200163 Experimental Design 4.0
200195 Information Systems Development 4.0
400082 Digital Analytics 7.5
400020 Information Systems Governance 3.5
200197 Brand Management 3.5
200070 Information Technologies Services Management 4.0
200071 Knowledge Management 7.5
200073 Information Systems Management 3.5
200193 Data Management and Storage 4.0
200196 Digital Marketing & E-Commerce 7.5
200189 Descriptive Analytics in Marketing 0.0
200165 Descriptive Methods of Data Mining 7.5
200192 Data Privacy, Security and Ethics 4.0
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
200190 Predictive Analytics in Marketing 7.5
200200 Search Engine Optimization 4.0
400081 Social Media Analytics 7.5
Options
200203 Machine Learning in Marketing 7.5
200210 Architectures for Information Systems 3.5
200202 Big Data for Marketing 7.5
200013 Business Intelligence II 7.5
200014 Business Process Management 3.5
200170 Consumer Behavior Insights 7.5
200049 Market Research 7.5
200068 Information Project Management 4.0
200190 Predictive Analytics in Marketing 7.5
200200 Search Engine Optimization 4.0
400081 Social Media Analytics 7.5
200194 Digital Transformation 3.5
2º year - Autumn semester
Code Name ECTS
200086 Research Methodologies 7.5
2º year - Spring semester
Code Name ECTS
200045 Internship 35.0