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Data Communication and Visualization


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


Overview/Description
The final step in the data science pipeline is to communicate the results or findings. In this course, you'll explore communication and visualization concepts needed by data scientists.

Target Audience
Individuals with some programming and math experience working toward implementing data science in their everyday work

Prerequisites
None

Expected Duration (hours)
1.3

Lesson Objectives

Data Communication and Visualization

  • start the course
  • choose appropriate visualization techniques
  • describe the difference between correlation and causation
  • define Simpson's paradox
  • communicate data science results informally
  • communicate data science results formally
  • implement strategies for effective data communication
  • use scatter plots
  • use line graphs
  • use bar charts
  • use histograms
  • use box plots
  • create a network visualization
  • create a bubble plot
  • create an interactive plot
  • find an appropriate data set in which a scatter plot represents it visually and plot it
  • Course Number:
    df_dses_a09_it_enus