Applied Time Series Analysis and Forecasting with R

Course Overview

What does this course tell?
(Please note that the following overview content is from the original platform)

R and time series analysis go together hand-in-hand. In this course, you'll learn how to effectively use R and the forecast package to practice time series analysis and work on real-world projects and data.

The R language and software environment are key when producing and analyzing time series data. In this course, Applied Time Series Analysis and Forecasting with R, you’ll learn how to apply modern day time series models on real-world data. First, you'll discover how to design time series models containing trend or seasonality. Next, you'll delve further into models, such as ARIMA, exponential smoothing, and neural networks. Finally, you'll learn how to visualize time series interactively with dygraphs. When you're finished with this course, you'll have the necessary knowledge to apply standard time series models on a univariate time series.
Topics:
Course Overview
Using R for Time Series Analysis
Modeling Unemployment Rates
Forecasting Inflation Rates
Predicting Sales Using Neural Networks
Course Summary and Further Learning
What can you get from this course?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
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What skills and knowledge will you acquire during this course?
This course provides learners with the skills and knowledge necessary to perform time series analysis and forecasting with R. Learners will gain an understanding of the fundamentals of time series analysis, including the use of R for time series analysis, modeling unemployment rates, forecasting inflation rates, and predicting sales using neural networks. Additionally, learners will learn how to use the forecast package for time series analysis and forecasting. After completing this course, learners will have the necessary knowledge and skills to apply standard time series models on a univariate time series.

How does this course contribute to professional growth?
This course provides a comprehensive introduction to time series analysis and forecasting with R, allowing learners to gain the necessary knowledge and skills to apply standard time series models on a univariate time series. By completing this course, professionals can develop their skills in time series analysis and forecasting, which can be applied to a variety of data science and analytics tasks. Additionally, learners can further their knowledge by exploring more advanced topics in time series analysis and forecasting, such as multivariate time series analysis, forecasting with ARIMA models, and forecasting with exponential smoothing. This course can also help professionals to explore related topics such as machine learning, data visualization, and data mining.

Is this course suitable for preparing further education?
This course provides a comprehensive introduction to time series analysis and forecasting with R, making it suitable for preparing further education. It covers the fundamentals of time series analysis, including the use of R for time series analysis, modeling unemployment rates, forecasting inflation rates, and predicting sales using neural networks. Additionally, the course covers the use of the forecast package for time series analysis and forecasting. After completing this course, learners can further their knowledge by exploring more advanced topics in time series analysis and forecasting, such as multivariate time series analysis, forecasting with ARIMA models, and forecasting with exponential smoothing. Therefore, this course is suitable for preparing further education in the field of time series analysis and forecasting.