Big Data Algorithms and Systems

LecturerProf. Dr. Siebert Andreas
Type of courseLecture / Tutorials
ECTS credits5
SemesterSummer semester
Admission RequirementsAlgorithms and data structures; programming knowledge
Objectives
  • Become familiar with basic algorithms in the field of big data and be able to apply them
  • Become familiar with systems that are used to process very large volumes of – in particular – unstructured data and be able to assess when it is appropriate to use them

Internet of Things

Internet of Things

LecturerProf. Dr. Abdelmajid Khelil, Dominik Obermaier
Type of courseLecture / Tutorials
ECTS credits5
SemesterSummer semester
Admission Requirements
Objectives
  • The syllabi will be communicated soon

Cloud Computing

Cloud Computing

LecturerProf. Dr. Markus Mock
Type of courseLecture
ECTS credits5
SemesterSummer Term
Admission RequirementsProgramming experience and a course in algorithms and data structures
Objectives
  • Become familiar with the importance of resource management and the concept of elasticity in the cloud
  • Learn about strategies for synchronizing distributed data sources
  • Explain the advantages and disadvantages of virtualized infrastructures
  • Become ready to launch an application that uses cloud infrastructure for processing or data storage in the cloud
  • Ability to structure an application appropriately between client and cloud rescources
  • Learn about important computing paradigms for highly distributed processing such as Mapreduce

Innovation Lab (IoT-Project)

LecturerProf. Dr. Abdelmajid Khelil
ECTS5
SemesterSummer
Admission RequirementsExperience in Software Enigneering and Programming
Objectives
  • Students will identify real-world problems and recognise the problems of creating complex solutions using a wide variety of IoT platforms. They are in a position to analyse the environment of the problem and are able to discuss these in advance in cooperation with companies.
  • Knowledge of design thinking, agile project management and the independent implementation of projects is acquired in teamwork. They are able to apply interdisciplinary knowledge, integrate the problem solver into the project in an agile manner and to present the results of their work.
Teaching Content

The cooperating companies offer the students real problems from the most important IoT domains, such as Smart Agriculture, Smart Building, Smart Energy, Smart Production, eHealth, etc.

The problem is described in detail using defined application cases. In addition, the aspects of IoT Cloud and IoT Security are also examined.
The students are supervised by the lecturer and the coach of the innovation lab.

Study Project

LecturerLecturers of CS
ECTS5
SemesterSummer
Admission RequirementsExperience in Programming and Software Engineeering
ObjectivesThe students know the problems of creating complex systems. They can apply the basics of scientific work and know how to independently carry out projects appropriate to the degree programme. They have learned to work in a team and have acquired knowledge in estimating the scope of projects as well as in the management and supervision of projects. They are able to apply interdisciplinary knowledge and present work results.
Course ContentThe teachers of the Faculty of Computer Science offer the students a choice of project topics with a short description. Teams of students can propose a project themselves, for this you must find a supervising lecturer. The students are regularly supervised professionally by the issuing lecturer.