Programme Overview

The Master’s programme in Data-driven Communication is a practice-based educational programme designed to meet to need in business, government and NGOs for specialists with professional knowledge and skills in data mining, digital marketing, PR and advertising.

The key aim of the programme is to develop students’ interdisciplinary competences in communication research, applied informatics and data science. Graduates will be qualified in:

• Big Data mining for planning, implementation and evaluation of communication campaigns in marketing, advertising and PR
• Applied and academic research based on data mining, large-scale network analysis, and agent-based models
• Open Data publication, visualization and interpretation as a new form of stakeholder communication

Programme advantages

The Master’s programme in Data-driven Communication is the first in Russia to train data scientists for the PR and advertising industry. The curriculum integrates communication studies and data science to provide students with a full range of professional competences for this emerging specialization. Acquired skills in data mining and machine learning can be applied to tasks encountered in communication industry practice, such as segmenting target audiences, predictive modelling of consumer preferences, algorithm design for programmatic advertising, and others. Students are also engaged in empirical mixed-methods communication research that combines data mining with other qualitative and quantitative methods.

Courses

Bridging courses:

• Digital PR and Advertising
• Basics of Applied Mathematics and Informatics

First-year basic courses:

• Basics of Data-driven Communication
• Web Communication Tools
• Programming for Computer Scientists
• Machine Learning and Data Mining

Second-year basic courses:

• Big Data for Communication Strategies
• Applied Network Analysis

The programme also offers a wide range of elective courses.

Skills and knowledge

• Advertising, marketing and PR
• Use of Big Data for planning, implementation and evaluation of communication campaigns
• Digital communication and web analytics
• Communication research using Big Data mining and other methods
• Machine learning, data mining, data visualization and predictive modelling in MATLAB, R and Python
• Data storage and management, grid and cloud computing
• Applied Network Analysis for communication research and digital PR