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