A case project where participants work in groups with a customer.
In this three week introductory course in Python for Data Science, the students will learn how to use Python libraries, Numpy and Pandas, in order to perform data manipulation through application of simple statistical models. Hence, the topics covered include some basic data manipulation techniques dealing with aggregation, descriptive statics, primarily visual, handling of missing data and “outliers”, and usage of simple statistical models, e.g. linear regression.
This is the first part of the MatchIt course series at Lund University. It is devoted to an introduction to Python for Scientific Computing within mathematics and technics.
This course is instructed by Claus Führer and Marlin Christersson assisted by Sadia Assim, Chiharu Kazama, Heidi Mach, Anna-Mariya Otsetova