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Python Programming in R-Programming
Module1:Introduction to R Programming
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    Quiz Icon 2 Quizzes
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    • 1.1.What is R?
       
    • 1.1.1. Introduction to R Language
       
    • 1.1.2. R's Role in Data Analysis
       
    • 1.2.Installing and Setting Up R
       
    • 1.2.1. Installing R on Different Platforms
       
    • 1.2.2. RStudio IDE Overview
       
Module 2:Basics of R Programming
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    • 2.1.Variables and Data Types
       
    • 2.1.1. Numeric, Character, Logical
       
    • 2.1.2. Vectors and Data Structures
       
    • 2.2.Basic Operations
       
    • 2.2.1. Arithmetic and Logical Operators
       
    • 2.2.2. Data Indexing and Sub setting
       
    • 2.3.Control Structures
       
    • 2.3.1. Conditional Statements (if, else)
       
    • 2.3.2. Loops (for, while)
       
Module 3:Data Manipulation with R
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    • 3.1.Reading Data into R
       
    • 3.1.1. Reading CSV, Excel, and Text Files
       
    • 3.1.2. Importing Data from Databases
       
    • 3.2.Exporting Data from R
       
    • 3.2.1. Writing Data to Files
       
    • 3.2.2. Exporting Data to Databases
       
    • 3.2.2. Closures
       
    • 3.3.Data Cleaning and Preprocessing
       
    • 3.3.1. Handling Missing Values
       
    • 3.3.2. Data Transformation
       
Module 4:Data Analysis with R**
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    • 4.1.Summary Statistics
       
    • 4.1.1. Descriptive Statistics
       
    • 4.1.2. Frequency Tables
       
    • 4.1.3. Thread Safety
       
    • 4.2.Data Visualization
       
    • 4.2.1. Futures and Promises
       
    • 4.2.1. Creating Plots with gplot2
       
    • 4.2.1. Creating Plots with ggplot2
       
Module 5:R for Data Science
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    Quiz Icon 1 Quiz
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    • 5.1.Introduction to dplyr
       
    • 5.1.1. Filter, Select, Mutate
       
    • 5.1.2. Group By and Summarize
       
    • 5.2.Data Visualization with ggplot2
       
    • 5.2.1. Advanced ggplot2 Concepts
       
    • 5.2.2. Creating Interactive Plots
       
    • 5.3.Working with Tidy Data
       
    • 5.3.1. Reshaping Data
       
Module 6:R for Machine Learning
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    Quiz Icon 1 Quiz
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    • 6.1.Types of Machine Learning
       
    • 6.1.1. Supervised Learning
       
    • 6.1.2. Unsupervised Learning
       
    • 6.2.Model Building with Caret
       
    • 6.2.1. Data Splitting and Cross-Validation
       
    • 6.3.Evaluating Machine Learning Models
       
    • 6.3.1. Performance Metrics
       
Module 7:Advanced R Programming
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    • 7.1.Functional Programming in R
       
    • 7.1.1. Functions as First-Class Objects
       
    • 7.1.2. Applying Functions with lapply and apply
       
    • 7.2.Object-Oriented Programming (OOP)
       
Module 8:R in Real-World Applications
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    • 8.1.Text Mining with R
       
    • 8.1.1. Text Preprocessing
       
    • 8.2.Time Series Analysis
       
    • 8.3.Shiny Web Applications
       
Module 9:Final Project and Course Review
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    Quiz Icon 1 Quiz
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    • 9.1.Project Proposal and Planning
       
    • 9.1.1. Selecting a Real-World Problem
       
    • 9.2.Implementation and Presentation
       
    • 9.2.1. Building and Deploying the Solution
       
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