Teaching



University Of Munich
  • Seminar on Databases: Distribution and Integration (winter term 2000/01)
    • Contents of the seminar: This seminar covers different aspects from the areas of distributed database management systems, database integration, federated database systems and data warehousing. Current work in these areas is discussed.
    • Responsibilities: Supervising the talks of the students, i.e. helping them understand the contents of the papers they will present, improving the structure of the talk and coaching the oral presentation.
    • Attendance: up to 15 graduate students.


  • Knowledge Dicovery in Databases (winter term 2000/01)
    • Contents of the class: Knowledge Discovery in Databases (KDD) is an interdisciplinary field bringing together techniques from various areas, e.g. machine learning, statistics, databases and visualization, to address the issues of analyzing huge data sets, and extracting knowledge from them. The birth of KDD was spurred by the rapid growth of almost all types of traditional (relational) and spatial databases, and the advent of commercial data warehouses, containing terrabytes of data, accumulated by established companies over the last decades. These mountains of data contain information from such diverse sources as credit card transactions, telephone calls, space observatories, human genome research, supermarket purchase transactions (market basket data) or web clickstreams. This class is an extended version of the course offered last winter term, with new and improved material from all areas. Again, the lecture will cover the standard knowledge discovery techniques from a theoretical perspective and the tutorial from the practical side.
    • Contents of the tutorial: The tutorial accompanying the KDD course is very hands-on and practical. Most of the assigments require the students to analyze a real-world data set using the commercial software "SPSS Clementine" and writing a short summary of the results of their analysis.
    • Responsibilities: Designing and teaching the accompanying tutorial.
    • Attendance: up to 20 graduate students.


  • Seminar on Knowledge Dicovery in Databases (summer term 2000)
    • Contents of the seminar: The seminar treats subject like association rules, classifikation, clustering, generalisation and the data cube. This years seminar covers more advanced topics and papers than the seminar the previous year.
    • Responsibilities: Supervising the talks of the students, i.e. helping them understand the contents of the papers they will present, improving the structure of the talk and coaching the oral presentation.
    • Attendance: 9 graduate students.


  • Knowledge Dicovery in Databases (winter term '99/'00)
    • Contents of the class: Knowledge Discovery in Databases (KDD) is an interdisciplinary field bringing together techniques from various areas, e.g. machine learning, statistics, databases and visualization, to address the issues of analyzing huge data sets, and extracting knowledge from them. The birth of KDD was spurred by the rapid growth of almost all types of traditional (relational) and spatial databases, and the advent of commercial data warehouses, containing terrabytes of data, accumulated by established companies over the last decades. These mountains of data contain information from such diverse sources as credit card transactions, telephone calls, space observatories, human genome research, supermarket purchase transactions (market basket data) or web clickstreams. We offered a brand new course covering all the standard knowledge discovery techniques from a theoretical perspective in the lectures and from the practical side in the tutorial.
    • Contents of the tutorial: The tutorial accompanying the KDD course is very hands-on and practical. Most of the assigments require the students to analyze a real-world data set using the commercial software "IBM Intelligent Miner" and writing a short summary of the results of their analysis.
    • Responsibilities: Designing and teaching the accompanying tutorial.
    • Attendance: 18 graduate students.


  • Seminar on Knowledge Dicovery in Databases (summer term '99)
    • Contents of the seminar: The seminar treats the standard knowledge discovery and data mining methods usually applied to data warehouses, e.g. association rules, classifikation, clustering, generalisation and ROLAP on the data cube.
    • Responsibilities: Supervising the talks of the students, i.e. helping them understand the contents of the papers they will present, improving the structure of the talk and coaching the oral presentation.
    • Attendance: 23 graduate students.


  • Database Management Systems (summer term '99)
    • Contents of the class: The basic course on database management systems covers all the hierarchical model, the network model, er-diagrams, relational algebra and calculus, the relational model and some transaction processing basics.
    • Contents of the tutorial: The purpose of the accompanying tutorial is to deepen the knowledge and to gain practical experience in designing and implementing problem database applications, e.g. designing entity-relationship diagrams and converting these into a relational schema in SQL notation for standard database management systems like ORACLE.
    • Responsibilities: Redesigning and teaching the accompanying tutorial.
    • Attendance: Approximately 60 undergraduate students.


  • Introduction to Computer Science II (summer term '98)
    • Contents of the class: The class 'Introduction to Computer Science II' is the second class for students of Computer Science at the University of Munich (LMU). The topics covered include: Sorting algorithms (simple sorting methods, divide-and-conquer methods, tree-based algorithms with performance considerations), graphs and graph algorithms (graph models, graph navigation, shortest-path problems) and searching techniques (exhaustive search, dreedy algorithms, backtracking, branch-and-bound techniques, divide-and-conquer methods and dynamic programming methods).
    • Contents of the tutorial: The main purpose of the accompanying tutorial is to deepen the theoretical knowledge and to gain practical experience in designing and implementing problem solving algorithms. For the latter reason many exercises were pracitcal programming problems using Modula-2.
    • Responsibilities: Designing and teaching the accompanying tutorial.
    • Attendance: Approximately 140 undergraduate students.




Stanford University
  • Transaction Processing (autumn quarter '96)
    • Contents of the class: Transaction management is one of the most crucial requirements for enterprise application development. Most of the large enterprise applications in the domains of finance, banking and electronic commerce rely on transaction processing for delivering their business functionality. Given the complexity of today's business requirements, transaction processing occupies one of the most complex segments of enterprise level distributed applications to build, deploy and maintain.
    • Responsibilities: Designing and teaching the course.
    • Attendance: 30 Ph.D and Master students on campus. The course was broadcast by SITN (Stanford Instructional Television Network) to numerous companies in the USA (e.g. Oracle, HP, Tandem, Sun). A total of 48 students took the class.



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