Description
Duration: 3 days
The purpose of this three-day course is to give students the knowledge needed to use Microsoft R Server to create and run an analysis on a large dataset, and how to utilize Microsoft R in Big Data environments. These environments are Hadoop, Spark cluster, and/or a SQL Server database.
This course is intended for IT professionals who wish to analyze large datasets within a big data environment. Additionally, IT developers who need to integrate R analyses into their solutions.
Upon completion of this course, students will be able to:
Explain how Microsoft R Server and Microsoft R Client work
Use R Client with R Server to explore big data held in different data stores
Visualize data by using graphs and plots
Transform and clean big data sets
Implement options for splitting analysis jobs into parallel tasks
Build and evaluate regression models generated from big data
Create, score, and deploy partitioning models generated from big data
Use R in the SQL Server and Hadoop environments
Prerequisites
In addition to their professional experience, it is recommended that students have:
Programming experience using R, and familiarity with common R packages
Knowledge of common statistical methods and data analysis best practices
Basic knowledge of the Microsoft Windows operating system and its core functionality
Working knowledge of relational databases.
What’s included?
- Authorized Courseware
- Intensive Hands on Skills Development with an Experienced Subject Matter Expert
- Hands-on practice on real Servers and extended lab support 1.800.482.3172
- Examination Vouchers & Onsite Certification Testing- (excluding Adobe and PMP Boot Camps)
- Academy Code of Honor: Test Pass Guarantee
- Optional: Package for Hotel Accommodations, Lunch and Transportation
With several convenient training delivery methods offered, The Academy makes getting the training you need easy. Whether you prefer to learn in a classroom or an online live learning virtual environment, training videos hosted online, and private group classes hosted at your site. We offer expert instruction to individuals, government agencies, non-profits, and corporations. Our live classes, on-sites, and online training videos all feature certified instructors who teach a detailed curriculum and share their expertise and insights with trainees. No matter how you prefer to receive the training, you can count on The Academy for an engaging and effective learning experience.
Methods
- Instructor Led (the best training format we offer)
- Live Online Classroom – Online Instructor Led
- Self-Paced Video
Speak to an Admissions Representative for complete details
| Start | Finish | Public Price | Public Enroll | Private Price | Private Enroll |
|---|---|---|---|---|---|
| 9/23/2024 | 9/25/2024 | ||||
| 10/14/2024 | 10/16/2024 | ||||
| 11/4/2024 | 11/6/2024 | ||||
| 11/25/2024 | 11/27/2024 | ||||
| 12/16/2024 | 12/18/2024 | ||||
| 1/6/2025 | 1/8/2025 | ||||
| 1/27/2025 | 1/29/2025 | ||||
| 2/17/2025 | 2/19/2025 | ||||
| 3/10/2025 | 3/12/2025 | ||||
| 3/31/2025 | 4/2/2025 | ||||
| 4/21/2025 | 4/23/2025 | ||||
| 5/12/2025 | 5/14/2025 | ||||
| 6/2/2025 | 6/4/2025 | ||||
| 6/23/2025 | 6/25/2025 | ||||
| 7/14/2025 | 7/16/2025 | ||||
| 8/4/2025 | 8/6/2025 | ||||
| 8/25/2025 | 8/27/2025 | ||||
| 9/15/2025 | 9/17/2025 | ||||
| 10/6/2025 | 10/8/2025 | ||||
| 10/27/2025 | 10/29/2025 | ||||
| 11/17/2025 | 11/19/2025 | ||||
| 12/8/2025 | 12/10/2025 | ||||
| 12/29/2025 | 12/31/2025 | ||||
| 1/19/2026 | 1/21/2026 |
Curriculum
Module 1: Microsoft R Server and R Client
Lessons
What is Microsoft R server
Using Microsoft R client
The ScaleR functions
Lab: Exploring Microsoft R Server and Microsoft R Client
Using R client in VSTR and RStudio
Exploring ScaleR functions
Connecting to a remote server
Module 2: Exploring Big Data
Lessons
Understanding ScaleR data sources
Reading data into an XDF object
Summarizing data in an XDF object
Lab: Exploring Big Data
Reading a local CSV file into an XDF file
Transforming data on input
Reading data from SQL Server into an XDF file
Generating summaries over the XDF data
Module 3: Visualizing Big Data
Lessons
Visualizing In-memory data
Visualizing big data
Lab: Visualizing data
Using ggplot to create a faceted plot with overlays
Using rxlinePlot and rxHistogram
Module 4: Processing Big Data
Lessons
Transforming Big Data
Managing datasets
Lab: Processing big data
Transforming big data
Sorting and merging big data
Connecting to a remote server
Module 5: Parallelizing Analysis Operations
Lessons
Using the RxLocalParallel compute context with rxExec
Using the revoPemaR package
Lab: Using rxExec and RevoPemaR to parallelize operations
Using rxExec to maximize resource use
Creating and using a PEMA class
Module 6: Creating and Evaluating Regression Models
Lessons
Clustering Big Data
Generating regression models and making predictions
Lab: Creating a linear regression model
Creating a cluster
Creating a regression model
Generate data for making predictions
Use the models to make predictions and compare the results
Module 7: Creating and Evaluating Partitioning Models
Lessons
Creating partitioning models based on decision trees.
Test partitioning models by making and comparing predictions
Lab: Creating and evaluating partitioning models
Splitting the dataset
Building models
Running predictions and testing the results
Comparing results
Module 8: Processing Big Data in SQL Server and Hadoop
Lessons
Using R in SQL Server
Using Hadoop Map/Reduce
Using Hadoop Spark
Lab: Processing big data in SQL Server and Hadoop
Creating a model and predicting outcomes in SQL Server
Performing an analysis and plotting the results using Hadoop Map/Reduce
Integrating a sparklyr script into a ScaleR workflow
