• Online, Self-Paced
Course 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.

Learning Objectives

Introduction to Data Communication

  • 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

Plotting

  • 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

Practice: Creating a Scatter Plot

  • find an appropriate data set in which a scatter plot represents it visually and plot it

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Data Administration
  • Systems Analysis