Scientific Programming

Full course description

Scientific programming can be seen like any other type of the laboratory experiment. During the experiment it is required to create a protocol, where each aspect of the experiment is properly described, so it can be reproduced with small experimental error every time it is done and independently of the user. The same applies to a scientific writing. The main objectives is to produce the results, which can be obtained independently of the user.

In this course, you will be introduced into several aspects relevant for programming and for working in the data science/machine learning filed. The course will introduce the relevance of automated statistical analysis, parallel computing, data visualization, interactive notebooks.

Format

The course follows the problem-based learning (PBL) approach. Characteristic of this approach is that learning is the result of an engaged interaction between academic staff and students, fuelled by their experience and knowledge, with the objective of developing understanding and insights.

The course consists of lectures, journal clubs and project meetings. Lectures and journal clubs are meant to introduce the specific topic and give broad understanding of its application and relevance. The project meetings are meant to give the opportunity to go more into depth of each presented subject. During those project meetings, the students will have an opportunity to apply the knowledge and extend it in the project under guidance of the supervisor. Here, the students will be solving problems to new situations by applying acquired knowledge, facts, techniques and rules in a different way.