Analyzing Big Data with Microsoft R E-Learning
Enroll in this unique online Fundamentals of Microsoft R course. Gain 1-year, 24/7 access to a dynamic e-learning environment featuring interactive videos, voice-guided instruction, progress tracking through reporting, and chapter-based quizzes to test your knowledge as you learn.
R is a widely used open-source programming language for data processing and statistical analysis. Microsoft R extends this power by offering a set of packages, interpreters, and infrastructure designed for scalable machine learning and data science solutions. With Microsoft R, you can work with large datasets without having to load them entirely into memory.
This training introduces Microsoft R, its core capabilities, and real-world applications. Designed for beginner to intermediate users, this course benefits data scientists, analysts, and statisticians across all industries.
Why Choose This Training?
- 1-year 24/7 access to interactive e-learning
- Learn at your own pace with guided video content and narration
- Includes chapter-based quizzes and progress monitoring
- Practical demonstrations and real-use scenarios
- Focused on scalable analysis of large datasets
- No prior Microsoft R experience required
Who Should Attend?
- Data analysts and statisticians new to Microsoft R
- Data scientists working with large-scale data
- IT professionals and business analysts exploring machine learning
- Anyone with basic data knowledge interested in scalable R-based solutions
Course content
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
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
