Python Lab

Course content

Aims

After successful completion of this module, students will have the competence to apply Python for designing and implementing small to medium software projects and analytic workflows with a focus on statistics and machine learning. During an interactive learning phase during which the students will be able to apply common packages such as scikit-learn, and they will be able to synthesize analysis workflows for diverse data science questions. These workflows will be presented and discussed in a mini-conference among the students. After the mini-conference, students will form small teams to develop data science software tools which will be presented during the closing event. They will gain the competence to critically evaluate machine learning workflows. 

Content

• Introduction to Python
• Introduction to explorative data analysis in Python
• Statistical data analysis
• Unsupervised machine learning
• Supervised machine learning
• Critical assessment of machine learning