DataCamp recently launched two new online R courses on time series analysis.

### Introduction to Time Series Analysis

What You’ll Learn:

- Chapter One:
**Exploratory Time Series Data Analysis****(FREE)**

Learn how to organize and visualize time series data in R. - Chapter Two:
**Predicting the Future**

Conduct trend spotting, learn the white noise model, the random walk model, and the definition of stationary processes. - Chapter Three:
**Correlation Analysis and the Autocorrelation Function**

Review the correlation coefficient, then practice estimating and visualizing autocorrelations for time series data. - Chapter Four:
**Autoregression**

Discover the autoregressive model and several of its basic properties. - Chapter Five:
**A Simple Moving Average**

Learn about the simple moving average model, then compare the performance of several models.

### Play now…

What You’ll Learn:

- Chapter One:
**Time Series Data and Models**

Investigate time series data and learn the basics of ARMA models, which can explain the behavior of such data. - Chapter Two:
**Fitting ARMA Models**

Discover the wonderful world of ARMA models and learn how to fit these models to time series data. - Chapter Three:
**ARIMA Models**

Learn about integrated ARMA (ARIMA) models for nonstationary time series. - Chapter Four:
**Seasonal ARIMA**

Learn how to fit and forecast seasonal time series data using seasonal ARIMA models.