R Programming
R Programming - base and advance
Course duration:
45 hours | 2 months (Live online/classroom training+ Projects + assignment/case studies + Interview preparation)
Training Mode:
Online & Classroom
Course Fees:
- Group training – INR 15000 | USD 450 (Other countries)
- Individual training – INR 30000 | USD 650 (Other countries).
Pre-requisites for R Course:
To attend this highly evolved R course, candidates must have basic understanding of maths and computer.
R Programming Certification:
At end of our course, you will be work on various projects. Once you completed assigned projects with expected results we will issue R Certificate.
Syllabus - program of study:
- How to Install R
- How to Install R, R Studio, and R Packages?
- Updating R and R Studio
- R Packages (Libraries)
- Recommended Packages
- Introduction to R Programming
- History of R language
- R programming features and limitation
- Comparison of R with other technologies
- Working with R scripts
- R Graphical User Interface (RGUI)
- Overview of R Studio
- Components of R Studio - code editor, visualization and debugging tools.
- Useful R packages
- Data types
- Data Structure
- Object
- Vectors
- Data frames
- Matrices
- List
- Importing Data from various sources – CSV, Text, Excel etc.
- Data frames and data sets in R
- Expressions, assignment, and arithmetic operations in R
- Exporting data to various formats
- Viewing data (viewing partial data and full data)
- Variable & value labels
- Data extraction
- Creating subgroups or bins of data
- Data type conversions
- Data formatting
- Applying transformations
- Applications of sub-setting data
- Duplicate data
- Missing data
- Sorting and ordering
- Filtering
- Creating new categorical variables - binning
- Reshaping data
- Sub-setting (rows and columns)
- Appending
- Merging/joining (Inner, Full, Left, Right etc.)
- Grouped expressions
- Variable and label renaming
- Conditional execution (if, if else etc.)
- Sampling data
- Loops (conditional, iterative loops, apply functions)
- Computing and adding new variables to a data frame
- R built-in functions (Text, Numeric, Date etc.)
- Numerical functions
- Text functions
- Date functions
- Utilities functions and R user defined functions
- Basics of exploratory data analysis
- Descriptive statistics - Frequency tables
- Univariate analysis - Distribution of data and graphical analysis
- Bivariate analysis - Cross tabulation
- Packages for exploratory analysis (dplyr, Hmisc, psych, crosstab etc.)
- About Markdown
- Chunking
- Knitr package
- Exporting (html, pdf, word, jpeg ,excel, csv etc.)
- Automated reporting
- Automated email sender
- Graphs and chart in R
- Bar graph
- Pie
- Histogram
- Box plot,
- Scatter plot etc.
- R packages for modern visualization - (ggplot2, Plotly, lattice etc.)
- Interactive graphs and charts
- Case studies
- Assignments
- projects with industry data.
- Case studies
- Assignments
- projects with industry data