Objectives

The aim of this course is to introduce students to the Jupyter Notebook which is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more. Through the notebooks, research results and the underlying analysis can be transparently reproduced as well as shared.

During three days with alternating video lectures and hands-on exercises, the participants will learn to construct well-documented, electronic notebooks that perform advanced data analysis and produce publication ready plots. While the course is based on Python, this is not a prerequisite, and many other programming languages can be used.

Dates

22 March 2021 until 26 March 2021

Personnel

Course organiser: Caterina Doglioni

Teachers: Mikael Lund

Pre-requisite/requirements

• Familiarity with programming concepts
• Basic knowledge of Python (recommended)/R/Julia
• Access to a desktop/laptop computer with
  • LINUX, MacOS or Windows
  • Anaconda or Miniconda installed - installation hints in the README of the course on GitHub
  • Internet connection

Additional information

Computational tools used: Jupyter notebooks, Anaconda, programming in Python, R of Julia

Course material is available on GitHub.

The course page at Astronomy and Theoretical Physics with access to the course plan.

Registration

Registration is now closed.