Kategorie: ‘Courses’

Datenbanken und Informationssysteme

March 27th, 2023 | by

Die Vorlesung “Datenbanken und Informationssysteme” gibt einen einführenden Überblick über Datenbanken und ihre Verwendung in Informationssystemen.

Data Stream Management and Analysis

March 17th, 2023 | by

In many fields today data is produced continuously, potentially unbounded, and at high rates, which is termed as data stream. Applications in smart manufacturing, aerospace,  particle physics, or stock exchange trading have a high demand to handle and analyze the massive data streams created. Due to their challenging characteristics specific technologies and methods for data management and analysis have been developed. In this course, you will get a deep understanding of these principles and techniques, such as query processing and optimization or data stream mining.

Seminar Computational Biomedicine

February 13th, 2023 | by

Integration of machine learning with medical data analysis is an essential block in the process of finding patient biomarkers used for clinical studies with a vision to improve cancer treatments. One such example is the application of personalized medicine, being one of the cornerstones for improving cancer patient care. In this Seminar, we will focus on the algorithmic and machine learning aspects of handling high throughput and high dimensional molecular data in the field of computation biomedicine.

Data Science in Medicine

January 26th, 2023 | by

Health data analytics is one of the main drivers for the future of medicine. Various sources of big data, including patient records, diagnostic images, genomic data, wearable sensors, are being generated in our everyday life by health care practitioners, researchers, and patients themselves. Data science aims to identify patterns, discovering the underlying cause of diseases and well being by analyzing this data.

Mixed Reality Lab

December 15th, 2022 | by

Mixed Reality is a continuum of spatial computing experiences on virtual, augmented and extended reality devices, such as the Microsoft HoloLens, the HTC Vive, and mobile phones. In this lab, we learn the basics of mixed reality software development in hands-on lessons with practical tasks. The lab contains a small independent project student groups can propose and work on.

Web3 Concepts and Applications

December 15th, 2022 | by

This seminar will discuss the baseline technologies and concepts of the web 3 such as Blockchain, Distributed Ledger, Tokenization, Self-sovereign identity, etc. as well as its applications e.g. in a Metaverse. After the seminar the participants will understand the Web3 Basics and will be able to develop concepts for new Web3 Applications.

Knowledge Graph Lab SS 2023

December 5th, 2022 | by

Knowledge Graphs are large graphs used to capture information about the real world in such a way that is is useful for applications. In these data structures, there are all sorts of entities (for example, people, events, places, organizations, etc.). Knowledge Graphs are used by many organizations to represent the information they need for their operations. The most well-known example is Google, where a knowledge graph is used to enrich the search results. Also personal assistants, such as Amazon’s Alexa, Apple’s Siri and Google Now, as well as question answering systems such as IBM Watson, make use of knowledge graphs to provide information to their users.

Besides these, also other information graphs, are in use by large organizations to improve or personalize their services. Examples include the Facebook graph, the Amazon product graph, and the Thompson Reuters Knowledge Graph.

Opensource Knowledge Graphs such as Wikidata and DBPedia provide universal access to linked entities from a large range of domains.

The graph also contains all sorts of information about these entities (e.g., age, opening hours, …) and relations between them (e.g., “this shop is located in Aachen”). Furthermore, it may contain context information (e.g., the source of some information) and schema information or background knowledge (e.g., “shops have opening hours”).

In this course we will give a basic practical introduction to working with these graphs. We plan to cover the following in the course:

  • Graph representation of data
  • Knowledge Graph basics
  • Knowledge Graph creation and maintainance tasks: Creation, Hosting, Curation and Deployment
  • Use of vocabularies and ontologies as schemas for graphs
  • Searching information in knowledge graphs
  • Information extraction into knowledge graphs
  • Data mining techniques for knowledge graphs
  • Knowledge graph completion (predicting links, finding anomalies)
  • Data governance aspects, e.g., data quality
  • Architectures for knowledge graphs (e.g., data lakes, central vs. decentral storage, knowledge graphs on top of relational or NoSQL databases)

Seminar Privacy and Big Data

December 1st, 2022 | by

This seminar is about new and emerging approaches to adjust and balance privacy and utility in data intensive applications, such as information retrieval, data mining and personalisation. These new approaches have the potential to enable a new generation of privacy-enabled services which are not focused on maximizing the collection of user data. Instead these new approaches enable user privacy under different threat models, such as protecting the identity of individual users when querying aggregated data, or preventing leakage of query patterns when users retrieve data from a database. As a result, these new approaches may help businesses in their compliance with increasingly regulatory trust and reinforce user trust, while enabling new business models at the same time.

Privacy Enhancing Technologies for Data Science

November 16th, 2022 | by

This lecture covers current research results in the area of Privacy Enhancing Technologies (PETs) which can be applied to Data Science. These PETs have the potential to enable a new generation of privacy-enabled services which are not focused on maximizing the collection of user data. We use a mix of recent book chapters and papers from conferences and journals of the last few years as primary source material.

Web Science Seminar

November 15th, 2022 | by

Web Science has become an interdisciplinary study field between computer science, mathematics, sociology, economics, and other disciplines. This seminar researches advanced Web Analytics and Web Engineering topics in Web Science probably leading to master thesis topics for excellent students. Topics include: network evolution models and network dynamics, (overlapping) community detection, recommender systems, adaptation and personalization in Web Environments, the Educational Web, Web Trust & Credibility, Web Protocols, Peer-to-Peer Networking for Web Clients, Web-based Software Development Models, particular Web Development methods like Web Components and many more. Students do not only learn to write and present scientific papers but also to peer review them. Students will be assigned to a supervisor helping the student through all steps like literature research, seminar paper and seminar presentation.