Data Science with R Programming Course Syllabus
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Syllabus for The Data Science with R Programming Course
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Module: 1 R Introduction
1
- Overview of R Programming
- Downloading and installing
- Help of Function
- Viewing documentation
- General issues in R
- Package Management
Module: 2 Data Inputting in R
2
- Data Types
- Subsetting
- Writing data
- Reading from csv files
- Creating a vector and vector operation
- Initializing data frame
- Control structure
- Re-directing R Output
Module: 3 Data Visualization
3
- Creating bar chart and dot plot
- Creating histogram and box plot
- Plotting with base graphics
- Plotting and coloring in R
Module: 4 Basic Statistic
4
- Computing Basic Statistics
- Comparing means of two samples
- Testing a proportion
- Data Munging Basics
Module: 5 Functions and Programming in R
5
- Flow control: For loop
- If condition
- Debugging tools
Module: 6 Data manipulation in R
6
- List Management
- Data Transformation
- Merging Data Frames
- Outlier Detection
- Combining multiple vectors
Module: 7 R an Database
7
- Performing queries
- RODBC and DBI Package
- Advanced Data handling
- Combined and restructuring data frames
Statistical Modelling in R
8
- Logical Regression
- Hierarchical Clustering PCA for Dimensionality Reduction
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