Introduction to Artificial Intelligence

Introduction to Artificial Intelligence

LecturerProf. Dr. Johannes Uhrmann
Type of courseLecture / Tutorials
ECTS credits5
SemesterSummer semester
Admission Requirements
Objectives
  • Basic Concepts, Predicate Logic, Inference Machines, Planning

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
Type of courseLecture / Tutorials
ECTS credits5
SemesterSummer semester
Admission Requirements
Objectives
  • The syllabi will be communicated soon

IT for Smart Grids

IT for Smart Grids

LecturerProf. Dr. Sascha Hauke
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