Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI
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Biostatistics & Epidemiological Data Analysis using R (Wintersemester 2023/2024)

Lecturer: Dr. rer. nat. Stefan Konigorski (Digital Health - Machine Learning)
Course Website: https://moodle2.uni-potsdam.de/course/view.php?id=39223

General Information

  • Weekly Hours: 4
  • Credits: 6
  • Graded: yes
  • Enrolment Deadline: 01.10.2023 - 31.10.2023
  • Examination time §9 (4) BAMA-O: 15.02.2024
  • Teaching Form: Lecture / Exercise
  • Enrolment Type: Compulsory Elective Module
  • Course Language: English
  • Maximum number of participants: 60

Programs, Module Groups & Modules

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
  • 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
Software Systems Engineering MA

Learning

  • Lectures with interactive practical exercises in R
  • Tutorials with discussion of homework

Dates

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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