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Coursera – Computing for Data Analysis

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Coursera – Computing for Data Analysis 

MP4 | 960 x 540 (1.778) @ 59.940 fps | Language: English | 715 MB Genre: eLearning

This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.

About the Course
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment, discuss generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.

A student who has completed this course is able to:

Read formatted data into R
Subset, remove missing values from, and clean tabular data
Write custom functions in R to implement new functionality and making use of control structures such as loops and conditionals
Use the R code debugger to identify problems in R functions
Make a scatterplot/boxplot/histogram/image plot and modify a plot with custom annotations
Define a new data class in R and write methods for that class

Coursera - Computing for Data AnalysisCoursera - Computing for Data Analysis

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