UnivIS
Informationssystem der Friedrich-Alexander-Universität Erlangen-Nürnberg © Config eG 
FAU Logo
  Sammlung/Stundenplan    Modulbelegung Home  |  Rechtliches  |  Kontakt  |  Hilfe    
Suche:      Semester:   
 
 Darstellung
 
Druckansicht

 
 
 Außerdem im UnivIS
 
Vorlesungs- und Modulverzeichnis nach Studiengängen

 
 
Veranstaltungskalender

Stellenangebote

Möbel-/Rechnerbörse

 
 
Vorlesungsverzeichnis >> Technische Fakultät (TF) >>

  Introduction to Complex Data Analysis in Python (KU) (OSS-ICDA-KU)

Dozentinnen/Dozenten
Michael Dorner, M. Sc., Prof. Dr. Dirk Riehle, MBA

Angaben
Kurs
, Sprache Deutsch und Englisch
Zeit und Ort: Einzeltermin am 16.4.2019 10:00 - 16:00, 04.150

Voraussetzungen / Organisatorisches
(Empfohlen)
  • Vorlesung: Algorithmen und Datenstrukturen,

  • Vorlesungen zu Statistik

Inhalt
Data analysis is an essential skill for computer scientists, researchers, and engineers. Complex data allow solving problems, which could not be solved only some years ago. However, with more and more complex data come complex data analysis pipelines and computational problem. In this hands-on, one-day workshop, we will work through the full cycle of data analysis: mining, importing, cleaning, transforming, joining, modeling, and analyzing complex data. For each step in the data analysis process, we will shortly discuss the necessary theoretical background, introduce the necessary tooling in Python, and apply this to a real world example from our current research.

The student needs prior experience in a modern programming language, with algorithm and data structures, databases, and statistics.

We will cover the following topics

  • 1) The Python programming language

  • 2) Graph theory and social network analysis

  • 3) Mining, importing, cleaning, transforming, joining, and modeling data, and the tools needed to perform these tasks those steps

  • 4) Complex data visualization

  • 5) Outlook on machine learning techniques

This course is organized as a one-day workshop. No ECTS are awarded. Participation is limited and registration is based on a first-come first-served basis.

The overall schedule can be found at https://goo.gl/AUw9B6 Please sign-up on StudOn to receive a seat (link available through schedule spreadsheet).

Zusätzliche Informationen
Erwartete Teilnehmerzahl: 10, Maximale Teilnehmerzahl: 30

Verwendung in folgenden UnivIS-Modulen
Startsemester SS 2019:
Software-Anwendungen mit KI (VUE 10-ECTS) (OSS-SAKI)

Institution: Professur für Open Source Software
UnivIS ist ein Produkt der Config eG, Buckenhof