Business Analytics

Description

Learning outcomes MMK1 Scientific-disciplinary knowledge and comprehension in the field of Artificial Intelligence MMI5 Entrepreneurship Objectives By the end of this course, the student understands how business problems can be formulated with advanced analytics techniques as a potential solution knows which data science tools and environments are available for realizing applications of machine learning in business is familiar with both classical and state-of-the-art time series forecasting techniques knows which business applications might benefit from deep learning techniques, and understands how to apply them and evaluate their appropriateness knows how to deal with unstructured data in the form of textual inputs, and use such data for practical business applications such as sentiment analysis understands how analytics techniques can exploit network-based information knows how analytical modeling techniques can be optimized and evaluated from a profit-driven perspective understands how prescriptive analytics and causal ML can help to use analytics for business decision making understands how process analytics can be applied to data sets originating from process-aware information systems understands how state-of-the-art explainability techniques can give insights into black-box machine learning models is able to reason on the organizational and managerial aspects of applying big data and analytics techniques