This course is part 2 of the Microsoft MCSA: Machine Learning course. The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database. During your 2-day training programme, you will live, learn at one of our state-of-the-art education centres. Using Insoftâ€™s uniqueâ€ŻLecture | Lab | Review technique, your expert instructor will immerse you inâ€ŻMicrosoft Official Curriculum, combined with practical exercises. After completing this course, you 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
At Insoft, we know your time is valuable. Thatâ€™s why we give you the opportunity to gain your Microsoft: Analyzing Big Data with Microsoft R training and certification in just 2 days. We provide the best conditions for you to learn and pass your exam. With us by your side, encouraging and guiding you along the way, you can enjoy 2 intense, focused days of quality learning in a distraction free environment. Your expert instructor will be working with Insoftâ€™s unique accelerated learning methods, which include our exclusive lecture/lab/review methodology with real life cases putting you in the best possible position to learn and retain knowledge. Sitting your Microsoft: Analyzing Big Data with Microsoft R course with Insoft means:
- Youâ€™ll get more hours of training per day, allowing you to get trained and certified faster and more cost-effectively than with any other training provider.
- You will be trained by one of the most expert instructors in the world.
- You can focus purely on learning in our distraction free environment.
- Dedicated onsite support and access to your classroom at all hours.
- The price you pay is all-inclusive and covers all course materials, exam, accommodation, meals and transportation service.
- The Certification Guarantee allows you to train again for free, if you do not pass first time. You only pay for any exams and labs, and accommodation.
This training already retired on 30th of June 2019.
Module 1: Microsoft R Server and R Client Explain how Microsoft R Server and Microsoft R Client work. 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 At the end of this module the student will be able to use R Client with R Server to explore big data held in different data stores. 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 Explain how to visualize data by using graphs and plots. 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 Explain how to transform and clean big data sets. 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 Explain how to implement options for splitting analysis jobs into parallel tasks. 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 Explain how to build and evaluate regression models generated from big data 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 Explain how to create and score partitioning models generated from big data. 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 Explain how to transform and clean big data sets. 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
Before taking this course you should 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.
Do you have what it takes? WeÂ´ll help you decide â€“ Call us to discuss your technical background, experience and qualifications to determine how we can help you succeed in this programme. Just call us and speak to one of our enrolment consultants.