Mastering R Programming

Simpliv

Course

Online

£ 20 + VAT

The best Other programming courses

See all

See all

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Build R packages, gain in-depth knowledge of machine learning, and master advanced programming techniques in R.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 video 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.We start off with pre-model-building activities such as univariate and bivariate analysis, outlier detection, and missing value treatment featuring the mice package. We then take a look linear and non-linear regression modeling and classification models, and check out the math behind the working of classification algorithms. We then shift our focus to unsupervised learning algorithms, time series analysis and forecasting models, and text analytics. We will see how to create a Term Document Matrix, normalize with TF-IDF, and draw a word cloud. We’ll also check out how cosine similarity can be used to score similar documents and how Latent Semantic Indexing (LSI) can be used as a vector space model to group similar documents. Later, the course delves into constructing charts using the Ggplot2 package and multiple strategies to speed up R code. We then go over the powerful `dplyr` and `data.table` packages and familiarize ourselves to work with the pipe operator during the process. We will learn to write and interface C++ code in R using the powerful Rcpp package. We’ll complete our journey with building an R package using facilities from the roxygen2 and dev tools packages.By the end of the course, you will have a solid knowledge of machine learning and the R language itself. You’ll also solve numerous coding challenges throughout the course.About the Author

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Perform pre-model-building steps
Get an in-depth view of linear and non-linear regression modeling
Build and evaluate classification models
Master the use of the powerful caret package
Understand the working behind core machine learning algorithms
Implement unsupervised learning algorithms
Build recommendation engines using multiple algorithms
Analyze time series data and build forecasting models
Delve in depth into text analytics
Interface C++ code in R using Rcpp
Construct nice looking charts with Ggplot2
Get to know advanced strategies to speed up R code
Build R packages from scratch and submit them to CRAN

Questions & Answers

Add your question

Our advisors and other users will be able to reply to you

Who would you like to address this question to?

Fill in your details to get a reply

We will only publish your name and question

Reviews

This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • How to Cook
  • Programming
  • Algorithms

Course programme

Pre-Model Building Steps 5 lectures 26:09 The Course Overview This video gives an overview of the entire course. Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
Pre-Model Building Steps 5 lectures 26:09 The Course Overview This video gives an overview of the entire course. Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. The Course Overview This video gives an overview of the entire course. This video gives an overview of the entire course. This video gives an overview of the entire course. Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Performing Univariate Analysis In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
In this video, we will take a look at how to perform univariate analysis.
  • Learn the use of univariate analysis on continuous variables and what the metrics are
  • Understand how to perform univariate analysis on categorical variables
  • See how to compute the metrics in R
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Bivariate Analysis – Correlation, Chi-Sq Test, and ANOVA The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
The goal of this video is to perform bivariate analysis in R using three cases.
  • Perform bivariate analysis using correlation analysis
  • Perform bivariate analysis using ANOVA
  • Perform bivariate analysis using the Chi-Sq statistic
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Detecting and Treating Outlier In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
In this video, we will see how to detect and treat outliers.
  • Check out how to detect outliers in a continuous variable
  • Get to know the ways to treat outliers
  • See how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
Treating Missing Values with `mice` The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
The goal of this video is to see how to treat missing values in R.
  • Understand the different types of missing values
  • Look at the ways to treat missing values
  • Check out how to code in R
Regression Modelling - In Depth 6 lectures 28:47 Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R.
  • The purpose of linear regression and the concept
  • How to build regression model in R
  • How to predict and compute accuracy measures.
Interpreting Regression Results and Interactions Terms We'll see how to interpret regression results and Interaction effects in this video
  • Explain the summary of regression results
  • Explain the various terms
  • Add interaction term to the model
Performing Residual Analysis and Extracting Extreme Observations With Cook's Distance In this video we will discuss what is residual analysis and detect multivariate outliers using Cook's Distance
  • Explain the meaning behind residual plots and its interpretation
  • Explain Cook's Distance, its meaning and significance
  • Implement them in R
Extracting Better Models with Best Subsets, Stepwise Regression, and ANOVA The goal of this video is to understand how to do model selection and comparison using best subsets, stepwise regression and ANOVA.
  • Explain Best subsets and do it in R
  • Stepwise regression
  • Compare models using ANOVA
Validating Model Performance on New Data with k-Fold Cross Validation In this video we will see how to do k-fold cross validation in R.
  • Explain the concept
  • Show how to implement it in R
Building Non-Linear Regressors with Splines and GAMs The goal of this video is check out how to build non-linear regression models using Splines and GAMs.
  • Explain the concept behind splines
  • Implement splines in R
  • Explain and implement GAMS
Regression Modelling - In Depth. 6 lectures 28:47 Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R.
  • The purpose of linear regression and the concept
  • How to build regression model in R
  • How to predict and compute accuracy measures.
Interpreting Regression Results and Interactions Terms We'll see how to interpret regression results and Interaction effects in this video
  • Explain the summary of regression results
  • Explain the various terms
  • Add interaction term to the model
Performing Residual Analysis and Extracting Extreme Observations With Cook's Distance In this video we will discuss what is residual analysis and detect multivariate outliers using Cook's Distance
  • Explain the meaning behind residual plots and its interpretation
  • Explain Cook's Distance, its meaning and significance
  • Implement them in R
Extracting Better Models with Best Subsets, Stepwise Regression, and ANOVA The goal of this video is to understand how to do model selection and comparison using best subsets, stepwise regression and ANOVA.
  • Explain Best subsets and do it in R
  • Stepwise regression
  • Compare models using ANOVA
Validating Model Performance on New Data with k-Fold Cross Validation In this video we will see how to do k-fold cross validation in R.
  • Explain the concept
  • Show how to implement it in R
Building Non-Linear Regressors with Splines and GAMs The goal of this video is check out how to build non-linear regression models using Splines and GAMs.
  • Explain the concept behind splines
  • Implement splines in R
  • Explain and implement GAMS
Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R.
  • The purpose of linear regression and the concept
  • How to build regression model in R
  • How to predict and compute accuracy measures.
Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R.
  • The purpose of linear regression and the concept
  • How to build regression model in R
  • How to predict and compute accuracy measures.
Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R.
  • The purpose of linear regression and the concept
  • How to build regression model in R
  • How to predict and compute accuracy measures.
Building Linear Regressors In this video we'll see what is linear regression, its purpose, when to use it, and how to implement in R heir usage
  • Show the concepts of cTree, rpart and C5.0
  • Implement in...

    • Additional information

    Basic knowledge of R would be helpful It assumes you are somewhat familiar working with the R language

    See related categories

    Mastering R Programming

    £ 20 + VAT

    The best Other programming courses

    See all

    See all