- Perform Data Preparation in R
- Know how to reset the dataframe index
- Deal with date-times in R
- Create, use, append, modify, rename, access and subset Lists in R
- Nest apply(), lapply() and sapply() functions within each other
- Basic knowledge of R
- Knowledge of the GGPlot2 package is recommended
- Knowledge of dataframes
- Knowledge of vectors and vectorized operations
R is a statistical programming language that allows you to build probabilistic models, perform data science, and build machine learning algorithms. R has a great package ecosystem that enables developers to conduct data visualization to data analysis.
This online course covers advanced-level concepts in R programming and demonstrates industry best practices. This is an advanced R course with an intensive focus on machine learning concepts in depth and applying them in the real world with R.
The course starts off with pre-model-building
activities such as univariate and bivariate analysis, outlier detection, and
missing value treatment featuring the mice package. Then we take a look at
linear, non-linear regression modeling and classification models, and will
check out the math behind the working of classification algorithms.
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