Winter School – Artificial Intelligence and Machine Learning (AI)

About

An increasingly complex global business environment requires firms to make use of the large amounts of data out there in order to make better decisions.

Machine learning allows to “automatically detect patterns in data, and then use the uncovered patterns to predict future data” (K. Murphy, Research Scientist at Google).

It is rapidly developing and changing businesses as well as companies’ financial processes. This opens up the possibility of using machine learning approaches to cope with complicated real-world financial problems.
All essential programming skills are taught in this course and there are no prior programming skills required. The course contains the following building blocks:

1. Introduction to AI and Machine Learning

2. Introduction to Python
Python Basics for Data Science
Importing and cleaning data
Natural language processing

3. Unsupervised Machine Learning
Dimensionality reduction techniques (e.g. hierarchical clustering)
Analyzing stock market data with K-Means Clustering
Topic modelling using Latent Dirichlet Allocation

4. Supervised Machine Learning
Fraud detection and loan default classification using k-nearest neighbors algorithm and support vector classification
Support vector regression to predict market prices
Performance evaluation of the prediction model

5. Data Analytics
Data description and visualization
Statistical analysis of socio-economic data

Target group

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

Course aim

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. For example, we will approach loan loss predictions or price and volume forecasts. Finally, the course gives you relevant data analytics skills such as the description, visualization and statistical analysis of such predictions. This is a hands-on class: We will use the programming language Python to apply the above concepts

Fee info