These notebooks are a new voluntary PC tutorial to accompany the lecture Economic Dynamics, which is part of the core curriculum of the economics MSc programmes at the university of Kiel. The lecture is based on the textbook by Gandolfo (2009) of the same title, and these PC tutorials follow the structure of the pen & paper tutorial.

As the structure is pre-determined, the first two tutorials are fairly simple, which might help students to familiarise themselves with the Python programming language and the Jupyter notebook environment. In the following three tutorials, covering differential equations, a number of time stepping methods are introduced, as well as Newton's method to find roots (steady states in the dynamic systems context). The last tutorial finally provides a glimpse into the world of numerical methods for dynamic optimisation, introducing a simple version of the forward-backward-sweep method.

Python was chosen as the programming language of choice due to its importance in scientific programming and data science, making it a relevant skill for economics students. The Jupyter notebooks are an ideal editor for these tutorials due to their ease of use and the features that allow adding detailed explanations with markdown formatting and Latex typesetting for equations between the code "cells". Implementations in other programming languages would be welcome too, as it would help those students who are interested in the methods and would prefer to implement them in e.g. MATLAB, Julia, or others, rather than having to learn Python basics first.

For MATLAB users, the tutorials and solutions are additionally provided as MATLAB scripts. The MATLAB tutorials are a work in progress, and some wrinkles should be expected.