Course: Fundamentals of Microsoft R

$259.00
$313.39 incl. vat
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duration: 15 hours |

Language: English (US) |

access duration: 90 days |

In Onbeperkt Leren

Details

In this online Microsoft R training you get started with Big Data features of Microsoft R. You will learn how to install and configure Microsoft R Server based on different databases and systems and you will get an introduction into R, data structures and types.
We also discuss big data processing concepts such as chunking algorithm. We also consider the import of data into Microsoft R from various data sources such as Hadoop, ODBC, SAS, SPSS, and SQL Server. And you get started with data manipulation techniques such as data sorting, merging, cleaning and filtering.
Among topics this course covers are Microsoft Machine Learning Server, RevoScaleR, control structures in R, XDF file, rxImport and far more.

Result

After successful completion you are familiar with the Big Data features of Microsoft R.

Prerequisites

No specific prior knowledge required.

Target audience

Data analist

Content

Fundamentals of Microsoft R

15 hours

Getting Started with Microsoft R

Microsoft R is a data analytics solution that

Packages and Data Types

This course covers features and components of Microsoft R Server, including its installation and configuration with various databases and IT systems. It also introduces the R language, including data structures and types.

The R Language and Big Data Processing

This course covers R programming language essentials, including subsetting various data structures, scoping rules, loop functions, and debugging R functions. It also covers big data processing concepts, including chunking algorithms.

Importing and Manipulating Data

This course covers loading data into Microsoft R from various data sources, including Hadoop, ODBC, SAS, SPSS, and SQL Server. It also covers data manipulation techniques, including data sorting, merging, cleaning, and filtering.

Modifying and Summarizing Data

This course covers data manipulation, including transforming XDF files, subsetting data, modifying variables, and converting data types. It also covers data summarization, including summary statistics and data exploration using Microsoft R.

Data Visualization and Predictive Analytics

This course outlines data visualization in Microsoft R, including basic principles and R functions used to create histograms, line plots, and bar charts. It also covers predictive analytics, including modeling techniques and key algorithms.

Regression Analysis

Regression Analysis

Decision Tree and Classification Analysis

This course covers key concepts regarding decision tree analysis and classification analysis using Microsoft R. Explore functions and techniques, including rxPredict, rxDForest, rxOneClassSvm, neural networks, and support vector machines.

Cluster Analysis and Ensemble Learning

This course covers key concepts related to cluster analysis using Microsoft R and the k-means clustering technique. It also covers ensemble learning for analysis, including random forest analysis.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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