To be confirmed. 

New course for 2023/24

This course is only available for students enrolled in the MPA - Data Science for Public Policy.  The course is not available as an outside option.

Students must have completed Pre-Sessional Coding and Mathematics Bootcamp (PP407).

This will ensure that students have basic fluency in Python and its main Data Science libraries. 

This course covers the theory and practice of the Data Science project lifecycle in Python for Public Policy, from problem definition and data sourcing/cleaning to exploration, visualization, and modelling. Emphasis will be placed on indentifying problems that are suitable for Data Science and on good practices for managing data. Linear and logistic models, regularization techniques and basic time-series models will be covered in the MT but more advanced timeseries and ML/AI models will be left for the LT. Key concepts and ideas underlying modelling (bias vs. variance, types of error, training vs. test data) and data ethics and data science ethics will be illustrated and implemented with examples from healthcare, education, urban policy, international development, and other policy areas. By the end of the course, students will have a strong coding workflow and will be able to source and experiment with data for their own analysis and research.

15 hours of lectures and 15 hours of seminars in the MT. 15 hours of lectures and 15 hours of seminars in the LT.

Students will be expected to produce 2 pieces of coursework in the MT and LT.

1. Jeffery CC. Chen, Edward A. Rubin, Gary J. Cornwall (2021) 'Data Science for Public Policy'. This book provides an excellent starting point and can be used as the main reference for many topics. A full reading list will be provided at the beginning of the course.

Exam (40%, duration: 3 hours, reading time: 15 minutes) in the summer exam period.
Coursework (30%), policy memo (15%) and presentation (15%) in the MT and LT.

Coursework is comprised of weekly coding notebooks to be completed by student. Students will also complete a policy memo, presentation and take a final exam for the course.