Course Details

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Modifying and Summarizing Data


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
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.

Target Audience
All individuals who wish to understand key concepts in big data analysis and Microsoft R features including scientists, analysts, and statisticians

Prerequisites
None

Expected Duration (hours)
0.9

Lesson Objectives

Modifying and Summarizing Data

  • start the course
  • describe the process of data transformation in Microsoft R
  • identify important functions and arguments used to modify data in Microsoft R
  • identify how to subset and transform data in Microsoft R
  • identify how to create or modify variables in Microsoft R
  • identify functions to transform data
  • describe what predictive analytics is
  • identify use cases of machine learning
  • recognize main branches and use cases of predictive models
  • recognize what machine learning is and identify its use cases
  • describe supervised and unsupervised learning techniques
  • list important techniques in predictive analytics
  • list the main steps in building a predictive analytics solution
  • identify important machine learning techniques
  • Course Number:
    df_abdr_a05_it_enus

    Expertise Level
    Intermediate