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.
Forecast bikeshare demand using time series models in R
2,561 already enrolled
Recommended experience
Objectives
Describe data to answer key questions to uncover insights
Fit well-validated time series models for forecasting future rental bikes demands
Provide analytic insights and data-driven recommendations
Skills you'll demonstrate
Details to know
Add to your Coursera profile
Use a Coursera Lab, a pre-configured in-browser cloud workspace (only available on desktop)
See how employees at top companies are mastering in-demand skills
About this Project
Project plan
This project requires you to independently complete the following steps:
Load and explore the data
Create interactive time series plots
Smooth time series data
Decompose and assess the stationarity of time series data
Fit and forecast time series data using ARIMA models
Offered by
Demonstrate your skills with Projects
Projects give you real-world challenges to solve with industry tools, and produce work samples that you can add to your Coursera Skills Profile to help you stand out to employers.
Manage my profileWhy people choose Coursera for their career
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy