Hasso-Plattner-Institut
  
Hasso-Plattner-Institut
Prof. Dr. Emmanuel Müller
  
 

Overview of Courses

In our lectures we cover basic concepts in the field of data analysis. The techniques for the analysis of large data sets have a large impact in many applications. The range of applications is broad and includes both industrial and scientific data. In both areas there is the necessity of extracting interesting patterns from very large datasets. In our courses we introduce the processing of large volumes of data as a precondition for quick and efficient analyses as well as the study of fundamental data mining techniques applicable to different domains.

  • Bachelor-Courses:
    Our courses "Big Data Analytics" and "Big Data Analytics Lab" will introduce the basic data mining challenges and propose different algorithmic solutions. 

  • Master-Courses:

    In Summer we plan further (advanced) courses: These courses will cover advanced data mining paradigms for complex data (starting Summer 2017) and advanced data structures for efficient data access in large databases (starting Summer 2016).    
    In Winter 2016/17 we plan an advanced lecture on "Graph Mining": This lecture will present data mining technology for large and complex networks (e.g. social networks, protein-interaction networks, and other types of networks).

  • Projects:
    Furthermore, we will offer Bachelor- and Master-Projects implementing the INTEGER teaching concept. These courses will cover practical challenges from industry and from interdisciplinary research collaborations.

  • Theses: 
    We offer several open research questions as Bachelor-/Master-Thesis. In each of these a novel data mining method will be developed, which solves an open challenge from an industrial or scientific domain. More information on each topic.

 

WinterSummer
Bachelor: Lecture
 "Big Data Analytics"
Project-Seminar
"Big Data Analytics Lab"
Bachelor-Project
"Predictive Diagnostics"
Master:Lecture
 "Graph Mining"
Lecture
 "Indexing Structures for Efficient Database Access"
Master-Project
"Interactive Exploration of Attributed Graphs"

Winter 2016/17

The lecture „Big Data Analytics“ will focus on data mining algorithms for knowledge discovery and covers the main steps of the Knowledge Discovery in Databases (KDD) process. We will introduce the basic data mining challenges and propose different algorithmic solution from each data mining sub-area. Furthermore, we will present basic evaluation methods which can be used to assess the quality of data mining results in various application areas.

  • Lecture Big Data Analytics (Bachelor)Course information and schedule
    Lecture hall HS 2 at HPI Campus I
    Wednesday (15:15 – 16:45) and Friday (09:15 – 10:45)
    Lecture starts Wednesday October 19th, 2016

 

  • Lecture Graph Mining (Master)Course information and schedule
    Room D-E.9/10 at HPI Campus II
    Tuesday (15:15 – 16:45)
    Lecture starts Tuesday October 18th, 2016

Summer 2016

The focus of our lecture „Indexing Structures for Efficient Database Access“ is on data structures to support efficient data access in large databases. The lecture includes data structures for one-dimensional, spatial, high-dimensional and metric data. We will discuss basic challenges for efficient data access and different algorithmic solutions for various data types.

 

  • Lecture Indexing Structures for Efficient Database Access: course information and schedule
    Hörsaal HS 2 at HPI
    Monday (09:15 – 10:45)

  • Project-Seminar Big Data Analytics Lab: course information
    Seminar room: D-E.9/10 and project room: E-1-03.2
    Monday (15:15 - 16:45)

  • Master-Project Interactive Exploration of Attributed Graphs: further information
    Project room: E-1-02.3

Winter 2015/16

The lecture „Big Data Analytics“ will focus on data mining algorithms for knowledge discovery and covers the main steps of the Knowledge Discovery in Databases (KDD) process. We will introduce the basic data mining challenges and propose different algorithmic solution from each data mining sub-area. Furthermore, we will present basic evaluation methods which can be used to assess the quality of data mining results in various application areas.

  • Lecture Big Data AnalyticsCourse information and schedule
    Lecture hall HS 2 at HPI
    Wednesday (15:15 – 16:45) and Friday (09:15 – 10:45)
    Lecture starts Wednesday October 14th, 2015

INTEGER Teaching Concept

INTEGER provides students (very early during their studies) the opportunity to participate in research. As part of lab courses, we supervise Bachelor and Master students w.r.t. open research challenges, development of novel solutions, publication of results, and let the student’s present their work at international conferences. With INTEGER students have successfully participated in the entire research process and gained enthusiasm for research.