Data Management and Engineering

This course provides a comprehensive introduction into a large variety of core topics related to data, data management, and data engineering. The quality of data and its management plays a central role in AI and data-driven systems, and has a direct impact on a system's effectiveness, efficiency, safety and reliability.

Therefore, the following topics are being covered:

• The role of data in AI systems

• Data Models and modelling data

• Discovering and creating large datasets

• Data quality and improving data quality

• Visually exploring data

• Integrating datasets

• Analyzing data with data mining techniques

• Visualizing data and analysis results

• Storing and retrieving data

• Distributing data

• Impact of inadequate data and data handing on subsequent systems and decision making

The final grade of the course consist of the following components:

• Written Exam (weighting 60%)

• Group Assignments: small-group projects focusing on practical skills and enabling key skills / professional skills (weighting 40%)

Final grade calculation = 0.6 * Written Exam + 0.4 * Group Assignments

A passing final grade for the course can only be earned when for all components at least a 5.0 is earned, and the weighted final grade is at least a 5.8.

In case of an insufficient final result, repair options may exist in accordance with Article 17A Times and number of examinations, sub 1, of the Teaching and Examination Regulations, for:

• Written Exam: Resit opportunity

• Group Assignments: Repair opportunity

Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).