Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI
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Applied data science on real-world hospital data (Sommersemester 2023)

Lecturer: Prof. Dr. Bernhard Renard (Data Analytics and Computational Statistics) , Ferdous Nasri (Data Analytics and Computational Statistics)

General Information

  • Weekly Hours: 4
  • Credits: 6
  • Graded: yes
  • Enrolment Deadline: 01.04.2023 - 07.05.2023
  • Teaching Form: Seminar
  • Enrolment Type: Compulsory Elective Module
  • Course Language: German
  • Maximum number of participants: 10

Programs, Module Groups & Modules

IT-Systems Engineering MA
Data Engineering MA
Digital Health MA
Cybersecurity MA
  • SECA: Security Analytics
    • HPI-SECA-K Konzepte und Methoden
  • SECA: Security Analytics
    • HPI-SECA-T Techniken und Werkzeuge
  • SECA: Security Analytics
    • HPI-SECA-S Spezialisierung
  • CYAD: Cyber Attack and Defense
    • HPI-CYAD-K Konzepte und Methoden
  • CYAD: Cyber Attack and Defense
    • HPI-CYAD-T Techniken und Werkzeuge
  • CYAD: Cyber Attack and Defense
    • HPI-CYAD-S Spezialisierung
Software Systems Engineering MA

Description

Within this course, we will work with hospital data from a collaboration partner to improve quality control processes. Students will implement software to interconnect data from different sources, design automated data analysis procedures, build dashboards for visualization, derive recommendations for decision makers in hospital regarding quality and discuss results with end users to iteratively improve performance.

Requirements

For this course you must have successfully passed the courses on Computational Statistics and Hierarchical Classification (or have equivalent knowlege explicitly approved by the teaching team before the first meeting of the course). Knowledge of German is required for the communication with project partners.

Participating in a pre-meeting with the external project partners during the semester break is strongly recommended.

Participants will need to sign a confidentiality agreement with project partners and agree to publication of code under a MIT licence.

Examination

Presentation (40%)

Final Report (60%)

Dates

Topics for projects will be introduced in the first meeting of the class, and students will send their preferred projects to the teaching team by the first week, projects will be assigned by the end of the first week, last time point to drop the class is April 28th 2023.

The first meeting will be on Thursday, April 20th at 11:00 am in room K-1.02. 

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