Analyzing Big Data with Microsoft R - R - Software Development / Ontwikkeling - Programmeren (algemeen) - Data Science - Data science met R - Functioneel programmeren

Analyzing Big Data with Microsoft R. 

Bestel deze unieke Elearning cursus Fundamentals of Microsoft R online, 1 jaar 24/ 7 toegang tot rijke interactieve video’s, spraak, voortgangsbewaking door rapportages en testen per hoofdstuk om de kennis direct te toetsen.

De open-source programmeertaal R is al lange tijd populair voor gegevensverwerking en statistische analyse. R heeft een beknopte programmeertaal en een uitgebreide repository van bibliotheken van derden voor het uitvoeren van allerlei soorten analyses. Microsoft R is een verzameling pakketten, tolken en infrastructuur voor het ontwikkelen en implementeren van op R gebaseerde oplossingen voor machine learning en datawetenschap. Met Microsoft R kunnen grote datasets worden verwerkt zonder ze allemaal tegelijk in het geheugen te hoeven laden. Dit pad introduceert Microsoft R, sleutelfuncties en hun toepassing op beginners- tot gemiddeld niveau waar datawetenschappers, analisten en statistici in alle organisaties van kunnen profiteren. De training geeft een beschrijving van de belangrijkste concepten en demonstraties.

Cursusinhoud

Introduction to Microsoft R

Course: 42 Minutes

• Course Introduction
• Overview of R
• Overview of Microsoft R
• Microsoft R Products
• Introduction to Microsoft R Client
• Installing Microsoft R Client
• Integrated Development Environments (IDEs) for R
• Microsoft R Interface
• R Studio Interface
• Visual Studio for R Interface

Practice: Features of Microsoft R

Course: 2 Minutes

• Exercise: Key Features of Microsoft R

Microsoft Machine Learning (ML) Server

Course: 32 Minutes

• Overview of Microsoft Machine Learning Server
• Microsoft ML Server Components
• Operationalize Analytics
• Operationalize Analytics Using Microsoft ML Server
• Supported Platforms for Microsoft ML Server
• Microsoft ML Server in the Cloud
• Compute Context

Practice: Microsoft R Server

Course: 2 Minutes

• Exercise: List Components of Microsoft R Server

Microsoft R Packages and Functions

Course: 43 Minutes

• Course Introduction
• Introduction to R Packages
• Introduction to Microsoft R Packages
• Introduction to RevoScaleR
• RevoScaleR Data Analysis Functions
• RevoScaleR Utility and Compute Functions
• Microsoft R vs. R Functions
• Introduction to MicrosoftML
• Introduction to mrsdeploy
• Introduction to olapR
• Introduction to sqlrutils

Practice: R Packages

Course: 2 Minutes

• Exercise: Features of the RevoScaleR Package

R Data Structures and Types

Course: 21 Minutes

• Introduction to the R Language
• R Objects and Attributes
• Vectors and Factors
• Matrices and Arrays
• Data Frames and Lists

Practice: R Data Structures and Types

Course: 2 Minutes

• Exercise: R Data Frames vs. Matrices

The R Language

Course: 51 Minutes

• Course Introduction
• An Overview of The R Language
• R Functions
• Operators
• Expressions
• Control Structures
• Loops
• Subsetting Vectors and Lists
• Subsetting Matrices and Data Frames
• Subsetting Operators
• Dates and Times
• Debugging R Functions

Practice: Using the R Language

Course: 1 Minute

• Exercise: Control Structures in R

Processing Big Data

Course: 44 Minutes

• Introduction to Big Data
• Big Data Analytics
• Applications of Big Data Analytics
• Microsoft R and Big Data Analytics
• Considerations for Big Data Analysis
• Creating an XDF File
• Splitting an XDF into Multiple Files
• Chunking Algorithms

Practice: Big Data Processing

Course: 2 Minutes

• Exercise: FeaturizeText

Loading Big Data into Microsoft R

Course: 41 Minutes

• Course Introduction
• Importing Data in Microsoft R
• rxImport Function
• Importing Text Data
• Importing Multiple Files
• Importing SAS and SPSS Data
• Importing SQL Server Data
• Importing HDFS Data
• Importing ODBC Data

Practice: Loading Data into Microsoft R

Course: 2 Minutes

• Exercise: Import Text Data into Microsoft R

Data Manipulation

Course: 23 Minutes

• Introduction to Data Manipulation
• Sorting Data
• Merging Data
• Subsetting Data

Practice: Data Manipulation

Course: 2 Minutes

• Exercise: Sort and Merge Functions

Modifying and Transforming Data

Course: 20 Minutes

• Course Introduction
• Data Transformation
• Modifying Data
• Creating a Variable
• Converting Data Types

Practice: Data Modification

Course: 1 Minute

• Exercise: Using Data Modification

Predictive Analytics

Course: 33 Minutes

• Using Predictive Analytics
• Predictive Analytics Applications
• Predictive Models
• Introduction to Machine Learning
• Supervised and Unsupervised Learning
• Machine Learning Techniques
• Process of Developing Predictive Models

Practice: Predictive Data Analysis

Course: 2 Minutes

• Exercise: Analyzing and Classifying Data

Summarizing Data

Course: 35 Minutes

• Course Introduction
• Introduction to Data Summarization
• Summarizing Qualitative Data
• Summarizing Quantitative Data
• Summarizing Bivariate Relationships
• rxCrossTabs Function
• rxCube Function
• rxSummary Function
• rxQuantile Function

Practice: Data Summarization

Course: 2 Minutes

• Exercise: Using Summary Statistics Functions

Data Visualization

Course: 18 Minutes

• Introduction to Data Visualization
• Data Visualization with R
• rxHistograms
• rxLinePlots

Practice: Visualizing Data

Course: 1 Minute

• Exercise: Using Data Visualisation Functions

Linear and Nonlinear Regression Analysis

Course: 31 Minutes

• Course Introduction
• Introduction to Linear Regression
• Linear Model Accuracy Measurement
• Microsoft R and Linear Regression
• Linear Regression Interpretation
• Nonlinear Regression

Practice: Linear Regression

Course: 2 Minutes

• Exercise: Linear Regression Functions

Logistic Regression Analysis

Course: 25 Minutes

• Introduction to Logistic Regression
• Logistic Model Accuracy Measurement
• Logistic Regression Interpretation
• Microsoft R and Logistic Regression

Practice: Logistic Regression

Course: 1 Minute

• Exercise: Logistic Regression Functions

Decision Tree Analysis

Course: 31 Minutes

• Course Introduction
• Introduction to Classification Algorithms
• Microsoft R's Classification Algorithms
• Naive Bayes Classifier
• Support Vector Machines
• rxOneClassSvm

Practice: Decision Trees

Course: 1 Minute

• Exercise: One-class Support Vector Machine
• Classification Analysis

Course: 26 Minutes

• Regression Trees
• Classification Trees
• rxDTree
• Visualizing Decision Trees

Practice: Using Classification Analysis

Course: 2 Minutes

• Exercise: rxDTree Function

Clustering Analysis

Course: 20 Minutes

• Course Introduction
• Unsupervised Learning
• Introduction to Clustering Analysis
• K-means Clustering
• rxKmeans

Practice: Using Clustering Analysis

Course: 1 Minute

• Exercise: rxKmeans Function

Ensemble Learning

Course: 41 Minutes

• What Is Ensemble Learning?
• rxEnsemble
• Random Forest
• Decision Forest
• rxFastTrees
• rxBTrees
• Neural Networks

Practice: Ensemble Learning Algorithms

Course: 1 Minute

• Exercise: Model Ensembles Metrics

Specificaties

Taal: Engels
Kwalificaties van de Instructeur: Gecertificeerd
Cursusformaat en Lengte: Lesvideo's met ondertiteling, interactieve elementen en opdrachten en testen
Lesduur: 10:05 uur
Voortgangsbewaking: Ja
Toegang tot Materiaal: 365 dagen
Technische Vereisten: Computer of mobiel apparaat, Stabiele internetverbindingen Webbrowserzoals Chrome, Firefox, Safari of Edge.
Support of Ondersteuning: Helpdesk en online kennisbank 24/7
Certificering: Certificaat van deelname in PDF formaat
Prijs en Kosten: Cursusprijs zonder extra kosten
Annuleringsbeleid en Geld-Terug-Garantie: Wij beoordelen dit per situatie
Award Winning E-learning: Ja

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