Data Analysis for Decision-Making 7.5 credits

The course develops the students’ ability to manage and/or conduct data-driven decision-making, in particular data analytics.The course includes the following elements: - Fundamental tasks in data analytics, i.e., classification, regression, clustering and association rules - Basic techniques for classification, regression, clustering and association rules - Organization of a data analysis project, i.e., preprocessing, modeling and evaluation - Software tools for data analytics - Research directions and state-of-the-art applications in data analytics - Data analytics applied to different business domains **Connection to Research and Practice** The course is based on the research areas of data analytics and machine learning, focusing on processes, techniques and algorithms. Students will learn standard scientific methods from data science, in particular the use of controlled experiments and statistical evaluation. The course also gives students an introduction to some relevant research directions and state-of-the-art applications in data analytics for digital business. The role of data in modern business and society is discussed extensively in the course. Examples and use cases in data analytics from the digital business domain, in particular marketing, sales and CRM, are used throughout the course, enabling students to gain knowledge about the real-world applications of the course’s theoretical concepts. The course also includes a substantial amount of practical work in a software tool for data analytics, including workshops, assignments and a data analytics project from the sales/marketing/CRM domain.