Programming for MNW

URL study guide

https://studiegids.vu.nl/en/courses/2025-2026/XB_0044

Course Objective

This is an introductory programming course based on the python language. It does not require previous programming skills. Some familiarity with the main statistical distributions (Gaussians, exponentials, etc), is helpful. The goals of the course are to enable the student to acquire the following skills: -install a software package, anaconda, on a personal computer
- execute python from "Jupyter Notebook"
- learn the basic commands in python, and transform them into working code to solve specific problems
- search for errors in a code (debugging)
- learn to use more elaborate tools that are made available by others (the libraries), and import them into one's codes
- develop simple mathematical models in programs to analyse and visualise experimental data.

Course Content

Starting from the very basic elements of python, very interesting computational problems can be solved. The knowledge is built from specific examples of data handling that are of interest for medicine or biology. The examples range from simply storing data, to implementing a mathematical model of the dynamics of a population from which an image is created, to describing and predicting exponential growth of a plague after contention measures are applied. At the end of the course the student will be able to create python scripts to solve some of the data analysis problems they are expected to find in the medical field.

Teaching Methods

The course is hybrid -
- it consists of one online lecture per week (via Zoom) and one exercise class per week (tutorial, in person). The students count with the support of teaching assistants daily via email, and during the tutorials. Additional 12 hours of self-study per week (based on online material) are required.

Method of Assessment

Throughout the course, the students develop python scripts (ungraded assignments) with the help of the teacher and teacher assistants. Although not graded, it is mandatory that the students work on all assignments, since they will serve as basis for the exam. The final exam consists in a set of exercises, similar to the ones developed in class.

Literature

All material is provided in Canvas

Target Audience

1MNW.

Entry Requirements

The course is meant to be followed by students with no previous programming experience. It is, however, mandatory that the students are able to run "Jupyter Notebook" from the very first lesson day, either using a digital platform or using a personal computer with an working installation of "Anaconda". Instructions are given in Canvas beforehand.

Explanation Canvas

Before the course starts, the student needs to follow the instructions given in Canvas to install "Anaconda" in a personal computer. The contents of each weekly module become available in Canvas at the end of the previous week.