Data Visualization for Scientists & Engineers
Track Data Analysis Track
Survey, explore, and create explanatory visualizations that facilitate communications with multiple techniques for visualizing data. By the end of the course, apply new skills to create a Jupyter notebook for exploring and explaining a scientific data set.
In the Data Visualization for Scientists and Engineers course, students will be exposed to multiple techniques for visualizing data.
There will be two main emphases through the course. First, how to survey and explore data to find gaps, interesting features, and places to explore more fully.
Second, how to create explanatory visualizations that facilitate communications.
The final portion of the course will consist of two hands-on projects in which students will create Jupyter notebooks for exploring and then explaining a scientific data set
This course requires basic proficiency with Python and the scientific Python stack. Some practical experience with Jupyter Notebooks, NumPy (ndarrays), Pandas (DataFrames), and scientific visualization in Python using Matplotlib are essential to working with the code and concepts presented in this course.
If you have taken Enthought’s Python Foundations for Scientists and Engineers, you have the requisite background knowledge for this course
Why Visualization? – Survey, Explore, Explain
Distributions – Distributions, Comparing Distributions
Relationships – Finding Relationships in Data
Multiple Dimensions – Handling More than Two Dimensions
Flow & Potential – Displaying Vector Fields, Map Underlays
Image Data – Visualizing Images & Other Raster Data
Graphs – Mapping Categorical Relationships
Animations – Animating Visualizations, Drill Downs
Exploratory Practicum – Project #1: Exploratory Visualization Notebook
Explanatory Practicum – Project #2: Explanatory Visualization Notebook
Enthought instructors have advanced degrees in scientific fields such as physics, engineering, computer science, and mathematics, and all have extensive experience through research and consulting in applying Python to solve complex problems across a range of industries, allowing them to bring their real world experience to the classroom every day.
cartopy, matplotlib, plotly, seaborn, stats-models
Download the syllabus for this course when you click here.
Interested in this course?
For more information, contact the Enthought Academy team.
Our Scientific Python Experts
Enthought Academy instructors are scientists and engineers themselves and have deep knowledge and understanding of the strategies and technologies covered in each track, and extensive practical experience applying Python to solve complex challenges across a range of science-based industries.
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