The course can be followed online if the student has a valid reason (approved by the program director) for not being able to show up for class. If classroom teaching is allowed, the student is expected to make every effort show up in the classroom.
Content. This course introduces the critical tasks of data collection and data wrangling, presentation and understanding of descriptive statistics and basics of visualization. The course focuses on classic statistics methods and their applications, such as data collection and sampling, generalization from the sample to the population and hypothesis testing.
Relevance. About 80% of data science tasks are composed of managing data, from understanding and altering features of the dataset and variables, to combining various datasets. Learning to manipulate and clean dataset, prepare for analysis and carry out exploratory data analysis are crucial skills for anyone set to carry out data analysis.