← Back to courses
Data Science and AI
Data Visualization with Python
Six weeks from arrays to an interactive dashboard
A six-week classroom course built on four libraries' own guides: NumPy's basics for beginners, the Matplotlib quick start, the seaborn tutorial and Streamlit's basic concepts. You go from arrays, to charts you control in detail, to statistical charts, to a small interactive data app. This course prepares for no exam.
8Modules
IntermediateLevel
6 weeksDuration
COURSE THUMBNAIL
What you will be able to do
Choose the right chart for a question
Control every part of a Matplotlib figure
Draw statistical charts with seaborn
Publish an interactive dashboard with Streamlit
Course outline
01
NumPy: arrays, indexing, operations and broadcasting
02
Matplotlib: the parts of a figure and the two interfaces
03
Matplotlib: styling, labelling, scales, ticks and colormaps
04
seaborn: statistical relationships and distributions
05
seaborn: categorical data, regression fits and multi-plot grids
06
seaborn: figure aesthetics and colour palettes
07
Streamlit: data, charts, widgets and layout
08
Project: a dashboard on a real dataset
Tools you will use
NumPyMatplotlibseabornStreamlitJupyter Notebook
What you need
Basic Python
Basic use of pandas helps
