Course details

Data Visualization and Predictive Analytics

Data Visualization and Predictive Analytics


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



Overview/Description
This course outlines data visualization in Microsoft R, including basic principles and R functions used to create histograms, line plots, and bar charts. It also covers predictive analytics, including modeling techniques and key algorithms.

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

Data Visualization and Predictive Analytics

  • start the course
  • recognize the concept of data summarization and its importance
  • identify important statistics used for summarizing quantitative data
  • identify important statistics used for summarizing qualitative data
  • describe univariate analysis and identify important functions
  • describe the rxCrossTabs function and its use cases
  • identify use cases of the rxCube function
  • recognize the rxSummary function and its use cases
  • identify use cases of the rxQuantile function
  • identify key functions that are used to produce summary statistics
  • describe data visualization and its importance
  • identify important R functions and packages for data visualization
  • recall how to create histograms in Microsoft R
  • specify how to create line plots in Microsoft R
  • identify key functions that are used to visualize data
  • Course Number:
    df_abdr_a06_it_enus

    Expertise Level
    Intermediate