InfoTekGuide

Summary:

 

This course is designed for beginners who want to learn R, a popular programming language for data analysis and statistics. Students will acquire fundamental programming skills in R and learn to manipulate data, create visualizations, and perform basic statistical analysis to leverage AI/ML algorithm to make data driven decisions.

 

Course Specifics:

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Introduction to R

• What is R?

• Installing R and R Studio

• Basic R syntax

• Variables and data types

• Simple calculations and operators​

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Working with Data in R

• Data structures in R: vectors, matrices, and data frames

• Data input and output

• Subsetting and indexing data

• Basic data manipulation

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​Control Structures and Functions

• Conditional statements (if-else)

• Loops (for, while)

• Writing and using functions

• Built-in functions in R

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Data Visualization with ggplot2

• Introduction to ggplot2

• Creating scatter plots, bar charts, and line graphs

• Customizing plot aesthetics

• Combining and faceting plots​

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Data Analysis with dplyr

• Introduction to dplyr

• Filtering and selecting data

• Grouping and summarizing data

• Joining datasets

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Introduction to Statistics with R

• Descriptive statistics

• Inferential statistics

• Hypothesis testing

• Linear regression

• AI/ML library with Association Rule, Clustering, Classification, Forecasting

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R Projects and Reproducible Research

• Organizing your R projects

• Version control with Git and GitHub

• Creating dynamic reports with R Markdown

• Sharing and collaborating on R projects

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Data Visualization Beyond ggplot2

• Customizing ggplot2 themes

• Interactive visualizations with Shiny

• Visualizing geographic data with leaflet

• Other R visualization libraries

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Final Projects and Course Wrap-up

• Students work on final projects applying what they have learned

• Project presentations and peer review

• Course review and next steps in R programming