Intro to Time Series Analysis in R
This course is perfect for anyone looking to learn the basics of time series analysis in R. In just 2 hours, you will learn the essential theory and build each of the major model types to forecast the future. You will also gain an understanding of the essential packages and functions in R to make time series analysis easy. Sign up now and start your journey to becoming a time series analysis expert! ▼
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Course Feature
Cost:
Paid
Provider:
Coursera
Certificate:
Paid Certification
Language:
English
Start Date:
24th Jul, 2023
Course Overview
❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [August 31st, 2023]
Skills and Knowledge:
-Understanding of essential theory for time series analysis
-Ability to build major model types (Autoregressive, Moving Average, ARMA, ARIMA, and decomposition)
-Knowledge of essential packages and functions in R for time series analysis
-Ability to forecast the future using real world data sets
-Understanding of how to apply time series analysis to real world problems
Professional Growth:
This course contributes to professional growth by providing the following benefits:
1. Enhanced analytical skills: Time series analysis is a valuable skill in various industries, such as finance, economics, and marketing. By completing this course, professionals can develop a solid understanding of the essential theory and techniques used in time series analysis. This knowledge can be applied to analyze and interpret complex data patterns, make accurate forecasts, and make informed business decisions.
2. Practical experience: The course is project-based, meaning that participants will have hands-on experience in applying time series analysis techniques to real-world data sets. This practical experience allows professionals to gain confidence in their ability to handle time series data and apply the learned concepts in their professional roles.
3. Familiarity with R packages and functions: R is a widely used programming language for statistical analysis and data visualization. This course introduces professionals to essential R packages and functions specifically designed for time series analysis. By becoming familiar with these tools, professionals can efficiently perform time series analysis tasks, saving time and effort in their professional work.
4. Forecasting skills: Forecasting future trends and patterns is crucial for businesses to make informed decisions and plan for the future. This course equips professionals with the knowledge and skills to build various time series models, such as autoregressive, moving average, ARMA, ARIMA, and decomposition models. By mastering these techniques, professionals can accurately forecast future values and trends, providing valuable insights for their organizations.
Overall, this course contributes to professional growth by enhancing analytical skills, providing practical experience, familiarizing professionals with essential R tools, and developing forecasting abilities. These skills are highly sought after in many industries and can lead to career advancement and increased job opportunities.
Further Education:
This course is suitable for preparing for further education. It provides an introduction to time series analysis in R and covers the essential theory and major model types. By the end of the course, you will have built models on a real-world dataset and learned about the essential packages and functions in R for time series analysis. This knowledge and skills can be valuable for further education in fields such as statistics, economics, finance, or data science.
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