The module Advanced Data Analytics for Management Support (ADAMS) introduces students to the latest developments in the scope of data-driven management support. It covers relevant theories and concepts in machine learning against the background of concrete real-world applications in management science. Special emphasize is given to the analysis of textual data and other forms of complex data such as sequences or images. Corresponding data is typically approached using the framework of deep artificial neural networks. The module recognizes the importance of deep learning and elaborates on corresponding methodologies. Frameworks and practices to use advanced (deep) machine learning technology and deploy corresponding solutions are of critical importance and will be elaborated in tutorial sessions.
The topics covered in the module include but are not limited to:
- Fundamentals of artificial neural networks
- Recurrent and convolutional neural networks for sequential data processing
- Fundamentals of natural language processing(NLP)
- Text embedding and language models
- Sentiment Analysis
- Approaches for NLP transfer learning
The module is designed as a follow-up to the module Business Analytics and Data Science (BADS). We expect students to have completed that module prior to taking ADAMS. More specifically, it is strongly recommended to join this module with a solid understanding of (supervised) machine learning practices and algorithms. Some experience in Python programming is also expected since we use the Python programming language in tutorials. The grading of the module will be based on a practical assignment, which also involves Python programming. |
