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Data Visualization

Asynchronous

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Registration Deadlines

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Category

Launch, Supplemental, Self-Directed, Mini-Course

Overview

Our materials touch on the following content to varying degrees:
• Plotting in Python: matplotlib, seaborn, plotly, and bokeh
• Web browser visualizations: HTML, CSS, SVG, and d3.js
• Basic Tableau
• Basic design principles

Organizers, Instructors, and Advisors

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Steven Gubkin

Head of Training and Assessment

Office Hours:

By appointment only

Email:

Preferred Contact:

Slack

Message me on Slack if you have questions about the course! I am also your primary contact for GitHub access.

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Matthew Osborne, PhD

Lead Instructor, Senior Operations Analyst

Office Hours:

None

Email:

Preferred Contact:

Slack

Please direct all course questions to Steven Gubkin.

Objectives

The aim of this mini course is to teach you how to produce data visualizations in a variety of programming languages/softwares while also touching on fundamental design principles. By the end of this mini course you will produce a portfolio worthy data visualization.

Slack

Slack Channel: #slack-channel

First Steps/Prerequisites

Participants should have a base-level familiarity with Python. If you are new to Python, but would still like to participate you can review our existing Python Prep materials to get up to speed. It will also be helpful, but not necessary to have a basic understanding of probability and statistics. If you would like to review some statistics or probability should check out the slides at these links: 

First Steps

Program Content

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Program Content

Textbook/Notes

Data Viz Mini Course Introduction

Introduction

In this video I provide a quick introduction to the mini course.

Transcript
Code

Project/Homework Instructions

In order to receive a certificate of completion you must submit a final project. Your final project should be a data visualization that you would be happy to show off in your data visualization portfolio. Projects can take a variety of forms including:

• An interactive dashboard,

• A data essay,

• A larger data visualization poster,

• A series of visualizations used as a part of your academic study,

• And more.

You may work by yourself or in small groups see the syllabus.pdf file

Project/Team Formation
Project Submission
Projects README

Schedule

Click on any date for more details

Please check your registration email for program schedule and zoom links.

Project/Homework Deadlines

To access the program content, you must first create an account and member profile and be logged in.

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