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

6th, 8th and 9th December 2022, 10:15 - 15:00 each day

In January there will be two days of project presentations.  The exact times will be organised with the participants.

Personnel

Teachers: Caterina Doglioni, Mikael Lund and Luis Sarmiento Pico

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.

Registration

Registration closes on 18 November 2022.

Registration is now closed.