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R

187

R is the open source programing language which is used for the analytic purpose. R can be used for several of statistical and machine learning purpose such as linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, and graphical techniques, and is highly extensible.

1,999
This course gives a basic introduction to R programming. R basic operations,vectors, data frames, lists and matrices. Data handling in R. Data importing, data sub-setting, data filtering, sorting, merging and removing the duplicates. Basic report generation, calculation of central tendencies, calculation of variance. Data exploration steps, data validation in R and data cleaning in R.

Course Currilcum

    • Handout – Introduction to R 00:00:00
    • 1.1 Getting Started in R FREE 00:00:00
    • 1.2 R Environment FREE 00:00:00
    • 1.3 R Packages 00:00:00
    • 1.4 R Data Types Vectors 00:00:00
    • 1.5 R Dataframes 00:00:00
    • 1.6 List in R 00:00:00
    • 1.7 Factor and Matrices 00:00:00
    • 1.8 R History and Scripts 00:00:00
    • 1.9 R Functions 00:00:00
    • 1.10 Errors in R 00:00:00
    • R quiz unit 1 Unlimited
    • Handout – Data Handling in R 00:00:00
    • 2.1 Data handling introduction FREE 00:00:00
    • 2.2 Importing the Datasets FREE 00:00:00
    • 2.3 Checklist 00:00:00
    • 2.4 Subsetting the Data 00:00:00
    • 2.5 Subsetting Variable Condition 00:00:00
    • 2.6 Calculated Fields _ ifelse 00:00:00
    • 2.7 Sorting and Duplicates 00:00:00
    • 2.8 Joining and Merging 00:00:00
    • 2.9 Exporting the Data 00:00:00
    • R Quiz Unit 2 Unlimited
    • Handout – Basic Statistics, Plots and Reporting in R 00:00:00
    • 3.1 Introduction and Sampling FREE 00:00:00
    • 3.2 Descriptive Statistics FREE 00:00:00
    • 3.3 Percentiles and Quartiles 00:00:00
    • 3.4 Box Plots 00:00:00
    • 3.5 Creating Graphs and Conclusion 00:00:00
    • R Quiz Unit 3 Unlimited
    • Handout – Data Cleaning and Treatment in R 00:00:00
    • 4.1 Data Cleaning Intro and Model Building Cycle FREE 00:00:00
    • 4.2 Model Building Cycle FREE 00:00:00
    • 4.3 Data Cleaning Case Study 00:00:00
    • 4.4 CS lab Step1 Basic Content of Dataset 00:00:00
    • 4.5 Variable level Exploration Catagorical 00:00:00
    • 4.6 Reading Data Dictionary 00:00:00
    • 4.7 Step2 lab Catagorical Variable Exploration 00:00:00
    • 4.8 Step3 lab Variable level Exploration – Continuous 00:00:00
    • 4.9 Data Cleaning and Treatments 00:00:00
    • 4.10 Step 4 Treatment – Scenario1 00:00:00
    • 4.11 Step 4 Treatment – Scenario 2 00:00:00
    • 4.12 Data Cleaning – Scenario 3 00:00:00
    • 4.13 Some Other Variables 00:00:00
    • 4.14 Conclusion 00:00:00
    • R Quiz Unit 4 Unlimited
    • Getting started with R 00:00:00
    • Data Handling on R 00:00:00
    • Basic Statistics in R 00:00:00
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