Learn how to create interactive plots and intelligent dashboards with Plotly, the Dash library and Python!
Created by Jose Portilla
Last updated 11/2018
What you’ll learn:
- In this course, you will learn how to use Plotly to create plots like bar charts, line charts, heat maps, scatter plots and more.
- You’ll learn to create layout with Ploty’s Dash library.
- You will also learn to create interactive components with Plotly using Dash.
- Connect multiple inputs and outputs with a dashboard
- Update live interactive graphs with clicks, hover and more
- connect the interactive admin access to live updating data for streaming information.
- Learn to secure your interactive dashboard with App Authorization.
- Deploy your interactive dashboards to the internet with services like Heroku.
- A little bit knowledge of Basic Python
- Computer with Internet Access
Welcome to Python Visualization Dashboards with Plotly’s Dash Library!
Passionate about creating your first application? This course will guide you through all the things you need to know in order to use Python to create interactive dashboard’s with Plotly’s new Dash library!
This is a chance to take your Python coding ability to the next level of data visualization. With this amazing course, you will be able to build fully customization, interactive dashboards with the open source libraries of Plotly and Dash.
Dash instructional courses from Plotly usually cost more than $1000, but now you can get the bootcamp experience for a fraction of that price in this self-paced course that includes example code, explanatory videos, student support in our chat channels, Question and Answer Forums, and interactive exercises.
You will begin this course with enough Numpy and Pandas that will make you feel comfortable while working and generating data in our quick crash course.
Also, you will be taught basic data visualization with Plotly, including scatter plots, line charts, bar charts, bubble charts, box plots, histograms, distribution plots, heat maps and more.
You will also be given an intuition of when to use each plot type.
By the time you are done with this course, learning the sharp edge of data visualization technology with Python. You would have gained some hot cake and demanding skill to showcase to your colleagues and potential employers.
After completing the course you will have a certification you can post to your LinkedIn profile and a portfolio of dashboard projects you can share as well.
- Python developers who are interested in learning how to create interactive dashboards and visualizations