R Programming: R for Data Science and Data Analytics A-Z™ Free Download

Description

Free Download R Programming: R for Data Science and Data Analytics A-Z™, with this course you will have the option to Learn R Programming Hands-on - Vectors and Data Frames, R Packages & Functions, R in Data Visualization, Apply R for ML. It contains 34 recordings. Remember that numerous understudies are tried out this course R Programming: R for Data Science and Data Analytics A-Z™, so don't hold on to download it presently, it's totally free. You can start learning R Programming: R for Data Science and Data Analytics A-Z™ by clicking the download link below.

Before you can start learning from this course explained in English (US) you need to have Knowledge of Basic Statistics, General idea how programing language works.

R Programming: R for Data Science and Data Analytics A-Z™ is targeting for people that have interset in Aspiring data scientists, Anyone interested in Statistical Analysis, If you want to learn R programming in easy steps, This course is for you if you are tired of R courses that are too complicated, This course is for you if you want to learn R Hands-on.

Finally you will learn how to Install R and R studio on Windows and Ubuntu machine, The core principles of R programming, Manage R Packages and working directory, Build user defined functions, R’s Decision Branching methods and loop operations, About Data types and Data structures, Operations on Vectors, Lists, Matrices, Arrays and Data frames, Manage data from External Sources (csv, Excel, JSON and XML files), Arrange Factor Data and the process of conversion ( vector to factor), Work with External Database, Visualize data in a structured way using ggplot2 package, Understand the statistical concepts (like Mean, Median, Correlation, Standard deviation, Normal Distribution) with proper R examples, Hypothesis testing in R ( t-test & Chi Squared Test ), The concept of Missing Value and their imputation process, Detect and Remove the outliers from data set, The concept, application, Mathematical computation and a complete data analysis using Simple Linear regression, Build and interpret a multiple linear regression model in R and also check the overall quality of the model, Generate a Logistic Regression Model, Predict the outcome from LR model and evaluate your model using Confusion Matrix and ROC- AUC Curve.

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