Biostatistics & Epidemiological Data Analysis using R (Wintersemester 2023/2024)
Dozent:
Dr. rer. nat. Stefan Konigorski
(Digital Health - Machine Learning)
Website zum Kurs:
https://moodle2.uni-potsdam.de/course/view.php?id=39223
Allgemeine Information
- Semesterwochenstunden: 4
- ECTS: 6
- Benotet:
Ja
- Einschreibefrist: 01.10.2023 - 31.10.2023
- Prüfungszeitpunkt §9 (4) BAMA-O: 15.02.2024
- Lehrform: Vorlesung / Übung
- Belegungsart: Wahlpflichtmodul
- Lehrsprache: Englisch
- Maximale Teilnehmerzahl: 60
Studiengänge, Modulgruppen & Module
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-K Konzepte und Methoden
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-T Techniken und Werkzeuge
- OSIS: Operating Systems & Information Systems Technology
- HPI-OSIS-S Spezialisierung
- DANA: Data Analytics
- HPI-DANA-K Konzepte und Methoden
- DANA: Data Analytics
- HPI-DANA-T Techniken und Werkzeuge
- DANA: Data Analytics
- HPI-DANA-S Spezialisierung
- CODS: Complex Data Systems
- HPI-CODS-K Konzepte und Methoden
- CODS: Complex Data Systems
- HPI-CODS-T Techniken und Werkzeuge
- CODS: Complex Data Systems
- HPI-CODS-S Spezialisierung
- Digital Health
- HPI-DH-DS Data Science for Digital Health
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-C Concepts and Methods
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-T Technologies and Tools
- SCAD: Scalable Computing and Algorithms for Digital Health
- HPI-SCAD-S Specialization
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-C Concepts and Methods
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-T Technologies and Tools
- DICR: Digitalization of Clinical and Research Processes
- HPI-DICR-S Specialization
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-C Concepts and Methods
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-T Technologies and Tools
- APAD: Acquisition, Processing and Analysis of Health Data
- HPI-APAD-S Specialization
- DSYS: Data-Driven Systems
- HPI-DSYS-C Concepts and Methods
- DSYS: Data-Driven Systems
- HPI-DSYS-T Technologies and Tools
- DSYS: Data-Driven Systems
- HPI-DSYS-S Specialization
Lern- und Lehrformen
- Lectures with interactive practical exercises in R
- Tutorials with discussion of homework
Termine
Lecture:
Wednesday Block (3:15pm-6:30pm), D.-E.9/10
Excercises:
Tuesday 5.00pm-6:30pm, online through zoom (link available below in timetable and in Moodle)
Link to Moodle where you can subscribe, find the zoom link and all other materials and information about the course: https://moodle2.uni-potsdam.de/course/view.php?id=39223
Timetable
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