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Foto: Matthias Friel

Data Science - Einzelansicht

Veranstaltungsart Vorlesung/Übung Veranstaltungsnummer 1101
SWS 4 Semester SoSe 2020
Einrichtung Wirtschaftswissenschaften   Sprache englisch
Belegungsfrist 20.04.2020 - 10.05.2020

Belegung über PULS
Gruppe 2:
     jetzt belegen / abmelden
    Tag Zeit Rhythmus Dauer Raum Lehrperson fällt aus am Max. Teilnehmer/-innen
Einzeltermine anzeigen
Vorlesung Sa 10:00 bis 12:00 wöchentlich 02.05.2020 bis 25.07.2020  3.06.S27 Dr. Evdokimov  
Einzeltermine anzeigen
Übung Mi 14:00 bis 16:00 wöchentlich 06.05.2020 bis 22.07.2020  3.06.S27 Baum  
Kommentar

The lecture and tutorial will be held via zoom. We will hold the sessions live. Questions can be asked via the chat. 

 

The lecture will take place each Saturday from 10:15 a.m. until 11:45 a.m., and the tutorial will be held each Wednesday from 2:15 p.m. until 3:45 p.m. 

 

The link to join the lecture / tutorial will be shared on moodle prior to the first sessions. 

 

 

Literatur

https://blog.coursera.org/5-data-science-books-read-2017/?utm_medium=email&utm_source=marketing&utm_campaign=xIppYP-pEea-CeWG7AzsXg

Voraussetzungen

Interest in data science. Basic knowledge of statistics. This class is limited to 18 students. The class will be held in English.

Leistungsnachweis

Written exam

Lerninhalte

 

Data is increasingly seen as a driving force behind many industries, ranging from data-driven start-ups to traditional manufacturing companies. Recent years have been marked by the hype around big data technologies and the implications that go along with it. In response to these developments, data science has become one of the most demanded specializations. Against this background, this class will introduce students to the fundamentals of data science, using Python. Specifically, the course will start with a short introduction into Python, covering such topics as syntax, basic data types, assignments and reference semantics, complex data types, functions, control of flow, modules, classes and objects, iPython, and debugging. In the next step, the students will be taught the basics of web scraping using Beautiful Soup library as well as learn to access data via dedicated APIs (Facebook, Twitter). In the follow-up sessions, the capabilities of NumPy, pandas, matplotlib, seaborn, and also Scikit Learn libraries will be explored to empower students with approaches to data analysis and visualization.


Strukturbaum
Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester SoSe 2020 , Aktuelles Semester: WiSe 2020/21