By Scientists for scientists

Data Visualization for Scientists & Engineers

Enthought Academy

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.

Course Hours20 hours

Course Overview

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

Prerequisite

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

Lectures

Why Visualization?Survey, Explore, Explain
DistributionsDistributions, Comparing Distributions
RelationshipsFinding Relationships in Data
Multiple DimensionsHandling More than Two Dimensions
Flow & PotentialDisplaying Vector Fields, Map Underlays
Image DataVisualizing Images & Other Raster Data
GraphsMapping Categorical Relationships
AnimationsAnimating Visualizations, Drill Downs
Exploratory PracticumProject #1: Exploratory Visualization Notebook
Explanatory PracticumProject #2: Explanatory Visualization Notebook

Instructors

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.

Packages

cartopy, matplotlib, plotly, seaborn, stats-models

Download the syllabus for this course when you click here.

Questions?

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.

Alexandre Chabot-Leclerc

Director, Operations

Mark Dickinson

Principal Engineer, Software Architecture

Sandhya Govindraraju

Senior Scientific Software Developer

Kuya Takami

Senior DTX Services Consultant and Instructor

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