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    Exams Included:

    • 70-773: Analyzing Big Data with Microsoft R

    TechSherpas ’ boot camps are geared towards providing students with the necessary skills and knowledge to not only pass the Microsoft Certification exams, but to also excel in their IT career paths. All of our boot camps are all-inclusive and include benefits such as:

    • 100% Test Pass Guarantee
    • All course materials, practice exams and official certification exams
    • Onsite Prometric Testing Center
    • Hands-on instruction by a certified instructor
    • Breakfast and Lunch provided each day
    • Airfare, lodging and transportation packages available (Option 2)


    Audience Profile

    Candidates for this exam are data scientists or analysts who process and analyze data sets larger than memory using R. Candidates should have experience with R, familiarity with data structures, familiarity with basic programming concepts (such as control flow and scope), and familiarity with writing and debugging R functions.


    At Course Completion

    After completing this course, students will be able to:

    • Deploy HDInsight Clusters.
    • Authorizing Users to Access Resources.
    • Loading Data into HDInsight.
    • Troubleshooting HDInsight.
    • Implement Batch Solutions.
    • Design Batch ETL Solutions for Big Data with Spark
    • Analyze Data with Spark SQL.
    • Analyze Data with Hive and Phoenix.
    • Describe Stream Analytics.
    • Implement Spark Streaming Using the DStream API.
    • Develop Big Data Real-Time Processing Solutions with Apache Storm.
    • Build Solutions that use Kafka and HBase.


    Course Description


    This accelerated boot camp will prepare students to pass the 70-773 exam, and gives 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.

    Read and explore big data

    • Read data with R Server
    • Summarize data
    • Visualize data


    Process big data

    • Process data with rxDataStep


    Perform complex transforms that use transform functions

    • Manage data sets
    • Process text using RML packages


    Build predictive models with ScaleR

    • Estimate linear models
    • Build and use partitioning models
    • Generate predictions and residuals
    • Evaluate models and tuning parameters
    • Create additional models using RML packages


    Use R Server in different environments

    • Use different compute contexts to run R Server effectively
    • Optimize tasks by using local compute contexts
    • Perform in-database analytics by using SQL Server
    • Implement analysis workflows in the Hadoop ecosystem and Spark
    • Deploy predictive models to SQL Server and Azure Machine Learning