Data Visualisation and Visual Analytics
Course overview
This course in data exploration and visualization covers cleaning and structuring datasets, and choosing suitable methods for visualizing them. It also provides theoretical knowledge of the underpinning descriptive statistics and the basics of human perception for cognition.
Learners will acquire skills in data exploration and visualization. By the end of the course they will be able to take raw data sets, clean them, structure them and choose suitable methods for visualizing them. They will also acquire theoretical knowledge of the underpinning descriptive statistics and the basics of human perception for cognition.
Who is this course for?
This is an introductory course on Data Visualization using Python, suitable for anyone with basic experience of Python programming.
Learning outcomes
By the end of this course you will be able to:
- Wrangle data (cleaning, integration) throughout a practical data pipeline (extract, transform, load phases)
- Aggregate data from large data sets
- Generate descriptive statistics
- Create numerical, categorical, geographic and hierarchical data visualizations
- Critically compare visualization techniques for their appropriateness to real data sets
- Create an applicable visualization pipeline, which takes into account human perception and cognition
License
This course is released under a CC BY 4.0 license.
It was designed by Professor Nick Holliman at Newcastle University.
It was designed by Professor Nick Holliman at Newcastle University.
