Summer 2016
Find out how to get access to eCampus here.
Undergraduate/Grundstudium
Projektgruppe
Wissensentdeckung und Maschinelles Lernen
Bachelor BA-INF 051
In dieser Projektgruppe werden grundlegende Algorithmen aus den Bereichen Maschinelles Lernen, Wissensentdeckung und Data Mining erarbeitet, diskutiert, implementiert und empirisch evaluiert.
Study Period: Undergraduate / Grundstudium
Lecturers: Prof. Dr. Stefan Wrobel, Dr. Tamas Horvath
Contact: Katrin Ullrich
Details
Prelim. Meeting: 2016-04-15, 14:00-15:00, room AVZ III / A 207
Time: Blockveranstaltung
You can access the materials to this course in eCampus
-
Dates: tba
In der Projektgruppe werden grundlegende Algorithmen aus den Bereichen Maschinelles Lernen, Wissensentdeckung und Data Mining vorgestellt. Die Aufgabe der Studenten ist es, in Kleingruppen sich jeweils einen Algorithmus zu erarbeiten und einen wissenschaftlichen Vortrag darüber zu halten. Im Anschluss soll der Algorithmus implementiert und evaluiert werden. Neben einem Abschlussvortrag soll eine schriftliche Ausarbeitung erstellt werden.
Ankündigung(en)
Die Vorbesprechung wird am 2016-04-15 um 14:00-15:00 in Raum AVZ III / A 207AVZ III / A207 (Römerstr. 164) stattfinden.
Graduate/Hauptstudium
Vorlesungen
Intelligent Learning and Analysis Systems: Data Mining and Knowledge Discovery
Master: MA-INF 4112
Introductory course to machine learning.
Study Period: Graduate / Hauptstudium
Lecturers: Prof. Dr. Stefan Wrobel, Dr. Tamas Horvath
Contact: Dr. Tamas Horvath
Details
Start date: 2016-04-22
Time: Fr 12:30-14:00 s.t.
Place: AVZ III / HS 1
Exercise time: Fr 14:00-16:00 c.t. (14:15-15:45)
Exercise place: AVZ III / A207 for group I; AVZ III / A301 for group II, AVZ III / HS1 for group III
Tutors:
- Linara Adilova (Group I, A207)
-
Lukasz Segiet (Group II, A301)
- Ivan Danielov Ivanov (Group III, HS 1)
You can access the materials to this course in eCampus
Description:
With more and more data available for analysis and decision making - from web documents and digital media to sensory data from cameras, microphones, and ubiquitous devices - it becomes increasingly more important to understand how such large volumes of data can be analyzed by computers and used as the basis for new intelligent services, for decision making, and for making computers learn from experience. In companies around the world, from retail and banks all the way to Google, intelligent learning and analysis techniques are used to improve business decisions. Likewise, in science, important discoveries are made easier by automated learning methods, and games and other artifacts are being made adaptive with learning technology.
Within the intelligent systems track of the computer science Master's program, intelligent learning and analysis systems are one of the two major topics. This module (Machine Learning) is one of the two modules that are offered as an introduction for master's students to Intelligent Learning and Analysis Systems. The other is the Data Mining module taught in the summer semester. Both modules can be selected in either order, and you may choose to attend one or both of them. For a complete introduction to the topic, it is recommended to attend both modules.
In the Data Mining module in particular, we will focus more on the algorithms for discovering knowledge in large databases and on their technical properties such as scalability. We will get to know scalable variants of the decision tree methods that we have been looking at in the Machine Learning module, and discover algorithms for new Data Mining tasks that we have not been looking at there, in particular clustering, association rule discovery, subgroup discovery, discovery from spatial and geographic data, analysis algorithm for text and web documents, visualization options for data analysis. We will mostly be focusing on practical and algorithmic aspects which can be tried out with popular Data Mining packages, but will also have a chance to look at some of the theory behind the algorithms.
Announcements
Important Dates
- midterm exercise checkup: 2016-07-01, in the exercise slot
- exam 1st try: 2016-08-05, 14:00-16:00 in HS 1+2 (Römerstr. 164)
- exam 2nd try: 2016-09-29, 14:00-16:00 in HS 1+2 (Römerstr. 164)
Data Science and Big Data
Master: MA-INF 4212
Advanced course on big data analytics and systems.
Study Period: Graduate / Hauptstudium
Lecturer: Dr. Tamas Horvath, PD Dr. Michael Mock
Contact: Dr. Tamas Horvath
Details
Start date: 2016-04-13
Time: Wed 14.30-16.00 s.t.
Place: AVZ III / A207
Exercise time: Wed 16:00-17.30
Exercise place: AVZ III / A207 and AVZ III / A121
Tutors: Alvin Tjondrowiguno
Description:
The course offers an
in-depth knowledge of different aspects of big data analytics and
systems, including algorithmic techniques for analyzing structured and
unstructured data that cannot be stored in a single computer because it
has enormous size and/or continuously arrives with such a high rate that
requires immediate processing. In addition to the algorithmic aspects, distributed big data processing and database systems will be presented and applied.
Topics include similarity search, synopses for massive data, mining massive graphs, classical data mining tasks for massive data and/or data streams, architectures and protocols for big data systems, distributed batch (Hadoop) and stream (Storm) processing systems, non-standard databases for big data (Cassandra).
recommended prerequisites:
MA-INF 4111 – Intelligent Learning and Analysis Systems: Machine Learning
MA-INF 4112 – Intelligent Learning and Analysis Systems: Data Mining and Knowledge Discovery
You can access the materials to this course in eCampus
Announcements
Important Dates
- midterm exercise checkup: 2016-06-22, in the exercise slot
- exam 1st try: 2016-07-28, 9:00-11:00 in HS 1 (Römerstr. 164)
- exam 2nd try: 2016-09-30, 9:00-11:00 in HS 1 (Römerstr. 164)
Seminar
Principles of Data Mining and Learning Algorithms:
Mining and Learning from Graph Structured Data
Master: MA-INF 4209
In this seminar we will discuss different state-of-the-art algorithms for graph mining or learning from graph structured data.
Study Period: Graduate / Hauptstudium
Lecturers: Prof. Dr. Stefan Wrobel, Pascal Welke
Contact: Pascal Welke
Prerequisites: MA-INF 4111 or 4112 or 4303 highly recommended
Preliminary Meeting: 2016-04-15, 13:00-14:00, room AVZ III / HS 1
Details
Prelim. Meeting: 2016-04-15 (Fr), 13:00-14:00, room AVZ III / HS 1
Time: block seminar
- Dates tba
Place: Schloss Birlinghoven (Sankt Augustin)
Description:
In this seminar we will discuss different state-of-the-art algorithms for graph mining or learning from graph structured data.
You can access the materials to this course in eCampus
Announcements
Important Dates
- preliminary meeting: 2016-04-15, 13:00-14:00, room AVZ III / HS 1
- 2016-06-14, 14:00-16:00. room IZB C1-214
- 2016-06-16, 14:00-16:00. room IZB C1-220
- 2016-06-21, 14:00-16:00. room IZB C1-214
- 2016-06-23, 14:00-16:00. room IZB C1-214
Praktikum
Lab Development and Application of Data Mining and Learning Systems
Master: MA-INF 4306
In this lab, machine learning and data mining techniques are implemented and used in a wide range of applications.
Study Period: Graduate / Hauptstudium
Lecturers: Prof. Dr. Stefan Wrobel, Katrin Ullrich
Contact: Katrin Ullrich
Prerequisites: MA-INF 4111 or MA-INF 4112 highly recommended
Preliminary Meeting: 2016-04-12, 14:00-16:00 in Schloss Birlinghoven, Sankt Augustin, in room B3-318
Important: if you are going to participate in the preliminary meeting, please send an e-mail to Katrin Ullrich
Details
Prelim. Meeting: 2016-04-12, 14:00-16:00 in Schloss Birlinghoven, Sankt Augustin, in room B3-318
Time: first Tuesday of every month
Place: Schloss Birlinghoven (Sankt Augustin)
Description:
In this lab, machine learning and data mining techniques are implemented and used in a wide range of applications.
You can access the materials to this course in eCampus
Announcements
- The preliminary meeting will take place on 2016-04-12 at 14:00-16:00 in Schloss Birlinghoven, Sankt Augustin, in room B3-318
Important Dates
Prelim. Meeting: 2016-04-12, 14:00-16:00 in Schloss Birlinghoven, Sankt Augustin, in room B3-318
