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To be confirmed

This course is compulsory on the MPA in Data Science for Public Policy. This course is not available as an outside option.

The bootcamp introduces students to coding and Data Science in Python and reviews key Math and Statistics topics for policy. It first introduces the building blocks of programming (variables, objects, conditions, loops, functions, etc) and some foundational libraries in Python (NumPy, Pandas, Matplotlib). It then covers basic data sourcing, data manipulation and (very) basic regression analysis in the contexts of simple applied policy exercises. It then devotes a week to refreshing key concepts in probability, statistics, linear algebra and optimization in Python. The final week focuses of moving from coding notebooks to packaged code, works on debugging, working in teams and provides a preview of ML, NLP and AI.

Exact hours of teaching will be confirmed when the programme Welcome schedules are prepared.

Students will attend lectures in the morning and then complete coding challenges throughout the day.

Students will be expected to produce coursework in August.

Students will complete daily coding challenges to apply new tools and concepts taught in the bootcamp. Most of these challenges will be on Jupyter notebooks.  

Prior to the start of the programming and mathematics bootcamp, students will receive a list of online resources to start learning basic computer programming on Python. These materials will emphasize basic syntax and programming logic.