You are here: Wiki>CompMolBio Web>Lectures>SciPro18 (17 Mar 2018, KatjaGeiger)Edit

Welcome to Scientific Programming with Python, summer term 2018

News

16.3.: Course starts 9 April, registration via email only, see below

General

Lecture-ID: 19226811
Lecturer: Frank Noé, Christoph Wehmeyer
Language: English
SWS: 2, LP/ECTS: 5, graded or ungraded depending on module

Requirements

This course is suitable for Master students of Mathematics, Computer Science, Computational Sciences, Physics

Registration

Due to the early date, registration for this seminar is via email, not Campus Management!
Registration deadline: Wednesday, April 4, 2018

E-Mail with Ref: "Registration 19226811 Python“ to christoph.wehmeyer[at]fu-berlin.de
Content: Full name, Student ID No (Matrikelnummer), study program, Zedat username.
If applications exceed available places, the registrar’s office will decide by lottery.
Students will be notified on Thursday, 5 April if they have a placement and will be added to the course roster manually.

Dates

Blockkurs/Compact Course 9 to 13 April 9-15 h Arnimallee 6 r. 030 (ground floor)

Hardware

Since the lab has a limited number of workstations, students will either have to share or bring their own notebooks.

Content

Python hat sich in den letzten Jahren zu einer der gängigen Programmiersprachen für Wissenschaftler entwickelt. Dieser Kurs gibt eine praxis-basierte Einführung in Möglichkeiten, gängige Probleme im wissenschaftlichen Alltag mit Python zu lösen. Der Kurs beinhaltet Themen wie Tools für die Entwicklung mit Python, Jupyter Notebooks, Visualisierung, moderne Programmierkonzepte, Lösen mathematischer Probleme und Maschinenlernen. Grundkenntnisse im Programmieren werden vorausgesetzt.

In recent years Python has become one of the most widely used programming languages in the scientific community. This course aims to be a "hands-on" introduction to solving common problems using Python. Topics included are tools for developing with Python, Jupyter notebooks, visualization, modern programming style, solving mathematical problems, and machine learning. A basic understanding of programming is mandatory for this course.
Topic revision: r2 - 17 Mar 2018, KatjaGeiger
 
  • Printable version of this topic (p) Printable version of this topic (p)