Forecast bikeshare demand using time series models in R

In this project, you’ll help a bike rental company enhance its fleet management and pricing strategy by building a daily bike rental forecasting model using time series analysis techniques in R. Your objectives include loading, cleaning, processing, and analyzing daily rental transaction data, and developing and evaluating time series models for the most accurate predictions. The company will use your validated forecasting model to determine the optimal number of bikes to keep in each station and set dynamic pricing based on predicted demand. Upon completion, you’ll be able to demonstrate your ability to perform a comprehensive data analysis project that involves answering critical business questions, extensive data visualization, and model selection. There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers. ROLE: Data Analyst SKILLS: R, RStudio, Data Analysis, Data Modelling, Time Series Modelling, Data Interpretation PREREQUISITES: Load, clean, explore, manipulate, and visualize data using R Write code in RStudio and R Markdown Knowledge of time series

• Project
• In this 4-6-hour project, you'll conduct a time series data analysis using R and upload your findings to your Coursera profile to showcase to potential employers.