M1: Data Handling, Exploration & Applied Machine Learning 10 ECTS
This module will prove a condensed introduction to the “Data Science Pipeline”, introducing students to methods, techniques, and workflows in applied data analytics and machine learning, including data acquisition, preparation, analysis, visualization, and communication.
M2: Network Analysis and Natural Language Processing 5 ECTS
Focuses on analyzing a variety of unstructured data sources. Particularly, students will learn how to explore, analyze, and visualize natural language (text) as well as relational (network) data.
M3: Data-Driven Business Modelling and Strategy 15 ECTS Course with integrated project in which you will learn how companies plan, prepare and execute data-driven projects. In the project you will work wich a company case and build a “mini” version of the product/process.
M3: (SDS) Deep Learning and Artificial Intelligence for Analytics 5 ECTS
Introduces to the most recent developments in machine learning, which are deep learning and artificial intelligence applications. The module will provide a solid foundation for this exciting and rapidly developing field. Students will learn whether and how to apply deep learning techniques for business analytics, and acquire proficiency in new methods autonomously.
Capstone Project Semester project utilising techniques and approaches from SDS in the context of a problem related to your main study field.