Data Science and Artificial Intelligence I

After reviewing the basics of Data Science and the Data Science Process, this course will give an overview of machine learning and other artificial intelligence methods in business applications. We will introduce, discuss, and apply hands-on different AI methods and tools, including currently trending function-based AI (Deep Learning methods), but also model-based AI (declarative problem solving), as well as hybrid approaches connecting the two worlds (e.g. Semantic technologies, Knowledge Graphs)  with a focus on solving business challenges in several case studies.

• The data science process

• Data Processing vs Data Analytics

• Function-Based AI and (Deep) Machine Learning

• Logic-based AI

• Hybrid and Explainable AI (e.g. Semantic Models)

Data Science and Artificial Intelligence II

This fast-paced class is intended for students interested data science
and artificial intelligence from a data and algorithmic governance
perspective.

The course focuses on gaining the fundamental knowledge necessary to
enable fair, transparent, explainable, and accountable data usage, with
a particular emphasis on the academic, industrial and societal relevancy
of the corresponding principles, tools, and technologies.

Students will understand the crucial role of data and algorithmic
governance when it comes to artificial intelligence and visa versa how
artificial intelligence tools, technologies, and techniques can
facilitate data and algorithmic governance.

Primary topics include:

• Ownership, control, and usage

• Fake news and misinformation

• Bias and fairness

• Transparency, explainability, and accountability