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Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

Posted By: serpmolot
Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language
English | November 2014 | mp4 | H264 1920x1080 | AAC 1 ch 125 kbps | 4 hrs 26 min | 3.17 GB
eLearning

Learn practical skills for visualizing, transforming, and modeling data in R. This comprehensive video course shows you how to explore and understand data, as well as how to build linear and non-linear models in the R language and environment. It’s ideal whether you’re a non-programmer with no data science experience, or a data scientist switching to R from other software such as SAS or Excel.

RStudio Master Instructor Garrett Grolemund covers the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. You’ll learn R’s syntax and grammar as well as how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.

All of the techniques introduced in this video are motivated by real problems that involved real datasets. You’ll get plenty of hands-on experience with R (and not just hear about it!), and lots of help if you get stuck.

Garrett Grolemund is a statistician, teacher, and R developer who works as a data scientist and Master Instructor at RStudio. He’s conducted corporate training in R at Google, eBay, Axciom, and many other companies, and is currently developing a training curriculum for RStudio. Garrett co-authored the lubridate R package and wrote the ggsubplot package. He received his Ph.D at Rice University.


Introduction to Data Science with R
Introduction to the Course 15m 29s

The R Language 1
Orientation to R 16m 39s
Data Structures and Types 16m 06s
Lists and Data Frames 18m 24s

The R Language 2
Subsetting 1 24m 15s
Subsetting 2 08m 02s
R Packages 05m 48s
Logical Tests 31m 19s
Missing Values 10m 55s

Visualizing Data
Introduction to ggplot2 07m 44s
Aesthetics 13m 45s
Facetting 07m 17s
Geoms 16m 24s
Position Adjustments 13m 06s
Visualizing Distributions 16m 43s
Visualizing Big Data 09m 05s
Saving Graphs 05m 46s

Adjusting Graphs
Visualizing Map Data 10m 14s
Titles and Coordinate Systems 11m 39s
Scales and Color Schemes 12m 12s
Themes 07m 07s
Axis Labels and Legends 09m 44s
Further Learning 03m 12s

Tidy Data
Reading in Data 09m 19s
Melt 12m 55s
dcast 08m 27s
rbind and cbind 02m 13s
Saving Data 04m 59s

Transforming Data
Line Plots 07m 17s
Filter and Select 04m 58s
Arrange, Mutate, and Summarize 07m 28s
Joining Data Sets 10m 53s
Grouping Data 08m 14s
The tbl Format 03m 06s
Advanced Manipulations 11m 28s

Modeling Basics
Introduction to Modeling 06m 22s
Linear Models and Model Syntax 16m 21s
Model Inference 15m 40s
Categorical Variables 07m 45s
Multivariate Models 18m 06s

Advanced Modeling
Introduction to Variable Selection 11m 17s
Best Subsets Selection 07m 21s
Stepwise Selection 11m 31s
Penalized Regression 04m 15s
Non-linear Models 19m 09s
Logistic Regression 10m 23s
Modeling Resources 02m 39s

Further Learning
Resources for R 03m 39s

Screenshots:

Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language

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Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language