Hasso-Plattner-Institut25 Jahre HPI
Hasso-Plattner-Institut25 Jahre HPI
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Medical Machine Learning Seminar (Sommersemester 2024)

Dozent: Prof. Dr. Christoph Lippert (Digital Health - Machine Learning)

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.04.2024 - 30.04.2024
  • Lehrform: Projekt / Seminar
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch

Studiengänge, Modulgruppen & Module

IT-Systems Engineering BA
  • ISAE: Internet, Security & Algorithm Engineering
    • HPI-ISAE-G Grundlagen
  • ISAE: Internet, Security & Algorithm Engineering
    • HPI-ISAE-V Vertiefung
  • SAMT: Software Architecture & Modeling Technology
    • HPI-SAMT-G Grundlagen
  • SAMT: Software Architecture & Modeling Technology
    • HPI-SAMT-V Vertiefung

Beschreibung

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Kick-off event on 11 April!

This seminar consists of semester-long research projects. The projects span topics from core machine learning research, such as generative models, uncertainty quantification, and interpretability; as well as applications in the biomedical and health sciences, such as epidemiological N-of-1 trials, genetics, and medical imaging. Students are expected to work closely with their individual supervisors (PhD students and PostDocs at the Digital Health - Machine Learning group), make substantial progress on their task, and give a presentation at the end of the semester. Especially successful projects may additionally lead to the publication of a scientific paper.

Students are required to have good coding skills (language will depend on the topic, but mostly Python and R) and have at least a basic understanding of modern machine learning, e.g. through the Deep Learning lecture at HPI or similar online courses.

project list link https://docs.google.com/spreadsheets/d/1o2W-5qLHpLeZ5B9Se45eGjoWtRwXC7BQegLmFDQg9n0/edit?usp=sharing

Voraussetzungen

Precise requirements differ between the different research projects. In all cases, basic skills in machine learning/deep learning and/or statistics are highly preferred. Ambitious students may take this seminar in parallel with the Introduction to Deep Learning course.

Literatur

project list link https://docs.google.com/spreadsheets/d/1o2W-5qLHpLeZ5B9Se45eGjoWtRwXC7BQegLmFDQg9n0/edit?usp=sharing

Leistungserfassung

Students will work on a project for the course, and the seminar will end with a short presentation and/or a short written report. Details to follow.

Termine

Kick-off event details:
When: 11th April, 9:15 a.m.
Where: pool room G2.U10/14
or via zoom using the below link:
https://zoom.us/j/5639734929?pwd=MWlnWStLRWVCdzk3eGhIb3dUTWlhUT09

Contact:teaching-lippert(at)hpi.de

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