Time Series Analysis & Forecasting in R Programming Language

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What Will You Learn?

  • Upon completing these modules, participants will be able to perform comprehensive time series analysis in R, including identifying and modeling trends, seasonality, and stationarity.
  • They will also gain proficiency in forecasting future values using both ARIMA and SARIMA models.
  • This series also aim to equip learners with the skills to leverage R Markdown for creating professional and visually appealing code presentations.
  • Furthermore, the series will cover techniques for enhancing the aesthetic appeal of R Markdown outputs, including image insertion, clickable links,
  • alongside efficient handling of code execution, tables, and images.

Course Content

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  • Files For Hands-On Learning

MODULE 1 OF 3: FOUNDATIONAL COURSE REVISION (Click to see module content)
A foundational course in R programming for data analytics typically covers the essential skills needed to manipulate, analyze, and visualize data using R.

MODULE 2 OF 3: R MARKDOWN- ADDING BEAUTY TO YOUR CODE PRESENTATION (Click to see module content)
This series aims to equip users with the skills to leverage R Markdown for creating professional and visually appealing code presentations. Objectives include mastering file management and knitting processes to generate HTML, Word, and PDF documents. Furthermore, the series will cover techniques for enhancing the aesthetic appeal of R Markdown outputs, including image insertion, clickable links, and basic website development principles, alongside efficient handling of code execution, tables, and graphs.

MODULE 3 OF 3: TIME SERIES ANALYSIS AND FORECASTING (Click to see module content)
Upon completing these modules, participants will be able to perform comprehensive time series analysis in R, including identifying and modeling trends, seasonality, and stationarity. They will also gain proficiency in forecasting future values using both ARIMA and SARIMA models.

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