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Data Science Data Science Fundamentals in R
Data Science Fundamentals in R

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Data Science Fundamentals in R

Brand: Data Science
€139,00 Excl. tax
€168,19 Incl. tax
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Data Science Using R E-learning

Fundamental Methods for Data Science in R


Course Introduction
What is Data Science?
Examples of Data Science
Sources of Data for Learning

Important R Basics

Data Frames
The Structure Function str
Summary Statistics
Import JSON Data
Foreach Looping

Data Management

Reshaping Data
Merging Data
Transposing Data
Aggregating Data
Basic Imputation
Linear Fitted Imputation
Categorize Continuous Variables

Data Analysis

Modeling for Data Science
Linear Modeling
Analysis of Variance
The R coef Function
The R fitted Function
The R residuals Function
The Variance-Covariance Matrix
Confidence Intervals
Fitting Generalized Linear Models
Plotting Linear Models
The TukeyHSD Test
The predict Function

Time Series

Time Series
The R forecast package

Practice: Data Science Fundamentals in R

Exercise: Using R for Data Science15 Minutes

Machine Learning Examples for Data Science in R


Course Introduction
Supervised and Unsupervised Learning


Multidimensional Scaling
Hierarchical Clustering
Hierarchical Clustering with corclust
K-Means Clustering
Selecting K for kmeans Clustering
Clustering Large Applications (Clara)
Fuzzy C-Means Clustering

Classification and Regression

Classification Trees with rpart in R
Regression Tree with rpart
Classification Trees with the tree Package
Regression Trees with the tree Package
K-Nearest Neighbor Classification
The randomForest Package
Combining Random Forests
Random Forests for Proximity Classification
Partitioning Around Medoids (PAM)
Naive Bayes Classifier
Linear Discriminant Analysis (LDA)
Quadratic Discriminant Analysis (QDA)
Mixture Discriminant Analysis (MDA)
Support Vector Machines (SVMs)
Loess Regression
Partial Least Squares Regression (PLS)
Smoothing Splines

Boosting and Bagging

AdaBoost in R

Advanced Visualizations

Scatterplot Matrix in R
Overlay Density Plots
Scatterplot 3D Visualization in R

Practice: Machine Learning Examples in R

Exercise: Statistical analysis in R


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General properties
Availabilty: 6 hours
Language: English
Certificate of participation: Yes
Online access: 90 days
Progress monitoring: Yes
Award Winning E-learning: Yes
Suitable for mobile: Yes
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