21 August 2020
Machine Learning and Data Analytics in Finance and Accounting
‘Big Data’ renders the global business environment increasingly complex requiring companies to look out for employees who are able to analyse large data, to detect patterns and to visualize results to decision-makers. Join the program on machine learning and data analytics to become an expert on real-world financial problems.
Prof. Dr. Thorsten Sellhorn
We offer this program for Bachelor students, Masters students and young scientists as well as to support their successful placement in attractive fields of activity.
There are no prior programming skills required. However, an interest in numbers and logical relationships as well as a basic statistical knowledge are advantageous.
Prerequisites for participation are a good command of written and spoken English. Lectures, presentations and examinations will be held in English. Even though we do not require students to submit language test results, we urge students with poor language skills to abstain from applying. Knowledge of German is not a prerequisite.
In the interest of maintaining the program's high standards, the number of participants will be limited to 30.
This course aims at making you familiar with basic machine learning approaches and data analytics techniques by enabling you to use them to your professional benefit. Adopting a user perspective, you will learn to automate simple, but time-consuming tasks such as classification of analysts’ conference calls into economically meaningful content.
Additionally, the course enables you to tackle complex prediction tasks using different information sources. Finally, the course gives you relevant data analytics skills such as the description, visualization and statistical analysis of such predictions. We will use the programming language Python to apply the above concepts. Upon successful application, participants will be able to analyse large amounts of data, receive 6 ECTS credits for their performance and explore Munich through extracurricular activities.
EUR 1200: Early Bird registration fee: € 100.00 (until March 1, 2020)
Registration fee: € 300.00
Tuition: € 1,100.00
Housing fee: € 430.00 (single room)