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

Forecast bikeshare demand using time series models in R

Instructor: Arimoro Olayinka Imisioluwa
3,777 already enrolled
What you'll learn
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 practice
- Interactive Data Visualization
- Revenue Management
- Predictive Analytics
- Data-Driven Decision-Making
- Business Strategy
- Trend Analysis
- Forecasting
- Data Processing
- Exploratory Data Analysis
- Data Visualization
- Machine Learning
- Data Manipulation
- Statistical Programming
- Time Series Analysis and Forecasting
- Predictive Modeling
- Data Analysis
- Data Cleansing
Tools you'll use
Details to know

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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these 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
Recommended experience
RStudio and R Markdown, Perform data manipulation and visualization using R, Prior experience with time series analysis
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Instructor

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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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