Predicting the number of bike shares in London

BSc project - 30 credits

Difficulty: Low/medium difficulty 😬 or 😬 😬, depending on specs

Description: We'll use data made publicly available from Transport for London (TFL; source of data: https://www.kaggle.com/datasets/hmavrodiev/london-bike-sharing-dataset) to estimate the relationship between the number of bikes shared around the London network on a given day, depending on weather and other characteristics to predict the capacity needed to satisfy demand at any given point. Requires R and familiarity with non-linear regression models. Students are encouraged to work with Rmarkdown or quarto to develop their dissertation.