Starting at USD 39.00
5 hours duration

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

This course offers an introduction to time series forecasting using R, a powerful tool for data-driven decision making. Forecasting plays a crucial role in various scenarios, from long-term capital investments to short-term scheduling. Accurate predictions are essential for making informed decisions based on data. In this course, you will learn how to create time series objects in R to analyze trends, seasonality, and repeated cycles. You will also explore the concept of white noise and conduct a Ljung-Box test to ensure randomness. To develop reliable forecast models, it is important to test and measure accuracy. This course covers various benchmarking methods and techniques for evaluating forecast accuracy. Furthermore, you will delve into exponential smoothing and ARIMA models, which are widely used in time series forecasting. These models will enable you to make accurate predictions based on historical data. Finally, you will discover how to enhance ARIMA models by incorporating additional information, such as holidays and competitor activity. By the end of this course, you will have the skills and knowledge to effectively use forecasting in R for data-driven decision making.

About Provider

DataCamp
DataCamp
Online Education Provider ยท 410 courses
Description
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.