• Introduction to Programming with Python
• Neural Networks (Feed-forward, Recurrent, and Convolutional) with applications for:
o Forecasting and classification of financial data
o Portfolio composition
o Identification of anomalies in financial data (using autoencoders)
o Generation of synthetic financial data (using GANs)
• Text Analysis
o Text summarization, word frequencies, topic modeling, word vectors
o Sentiment analysis and text classification
o Text analysis of annual reports, earnings calls, and financial news

The methods of deep learning and text analysis were originally developed for use in other scientific disciplines—such as image recognition or, for instance, the operation of chatbots. Nevertheless, an increasing number of recent applications and publications suggest that these methods hold great potential for the business sector. The objective of this course is to foster a fundamental understanding of the inner workings of the methods covered herein, as well as to identify and explore their potential applications within the field of economics and business.