course: Fundamentals of Data Science

number:
141213
teaching methods:
lecture with tutorials
media:
computer based presentation
responsible person:
Prof. Dr.-Ing. Aydin Sezgin
lecturers:
Prof. Dr.-Ing. Aydin Sezgin (ETIT), M. Sc. Aya Ahmed (ETIT)
language:
english
HWS:
4
CP:
5
offered in:
summer term

dates in summer term

  • lecture: Tuesday the 10.04.2018

Exam

Oral

Date according to prior agreement with lecturer.

Duration: 30min
Exam registration: FlexNow

goals

The stu­dents un­der­stand the con­cepts of pattern recognition, machine learning, and information theory and are able to apply it to data analysis. Equip­ped with tools and me­thods ac­qui­red du­ring the lec­tu­res, problems arising regularly in engineering disciples can be in­ves­ti­ga­ted.

content

  • Introduction
  • Review: Linear Algebra
  • Review: Probability Theory, Random variables and processes
  • Discovery of regularities in data via Pattern recognition
  • Development of algorithms via Machine learning (Classification, Clustering, Reinforcement Learning)
  • Performance criteria via Information theory

requirements

none

recommended knowledge

  • Math I-IV
  • System theory I-III
  • Optimization