Build an Interactive Data Analytics Dashboard with Python
This course teaches you all of the skills to build interactive data analytics dashboards with Python. You will be building a Coronavirus Forecasting Dashboard displaying historical and predicted deaths and cases for all countries and US states during the ongoing coronavirus pandemic. The final product will be a live dashboard, automatically updated daily, hosted on a remote server for anyone, anywhere in the world to see!
Start Building the Dashboard Now!Visit the Live Dashboard Now!
You will be building the Coronavirus Forecasting Dashboard that can be viewed live at coronavirus-project.dunderdata.com.
Course Overview
Get an overview of the dashboard and course contents
Course Content
The course is divided into the following parts covering every facet of building a dashboard for use in a professional environment. There are 12 hours of video lectures walking you through all of the content.
Getting, Cleaning, and Transforming the Data
You will learn how to collect the data, find and clean bad data, and transform it so that it can be used for building models capable of prediction.
Data Smoothing
You will learn several different techniques such as LOWESS to smooth the jagged raw data so that the model can better detect trends.
Exponential Growth and Decline Models
You will begin modeling coronavirus cases for each area of the world with these simple models that can capture a single exponential growth or decline phase, but not both.
Logistic Growth Models
You will learn about a separate class of "S-Curve" models capable of capturing both exponential growth and decline in the same model.
Modeling New Waves
Coronavirus cases appear in waves over different time periods. You will learn how to change your model so that it can detect any number of new waves in the future.
Encapsulation into Classes
After selecting your model, you will encapsulate all of the code together into Python classes, eventually to be used in your final production code.
Visualizations with Plotly
You will learn how to use the Plotly Python library to create interactive data visualizations targeted for the web
HTML and CSS
You are building a web application and will learn the fundamentals of HTML and CSS to help add customization with the help of Dash.
Building the Dashboard with Dash
You will learn how to build all of the components and interactivity of the dashboard with the Dash Python library.
Deployment
One of the most exciting parts of a project is deploying it on your own server for the world to see. You will learn two different deployment options - one simple and the other more complex, but with more flexibility.
What this course includes
This course comes with a massive amount of material including:
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13 Jupyter Notebooks
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26 Exercises with detailed solutions
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200 page PDF of the entire course content
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All production code for the dashboard
- 12 hours of video lectures walking you through all of the content
About the Instructor
This course is taught by Ted Petrou, an expert at Python, data exploration and machine learning. He is the author of multiple highly rated texts including:
- Pandas Cookbook
- Master the Fundamentals of Python
- Master Data Analysis with Python
- Master Machine Learning with Python
- Build an Interactive Data Analytics Dashboard with Python
Ted has taught hundreds of students Python and data science during in-person classroom settings. He sees first hand exactly where students struggle and continually upgrades his material to minimize these struggles by providing a simple and direct path forward.
Ted is one of the foremost authorities on using the pandas library to do data analysis. His blog posts have totaled well over 1 million views. He is also a prolific contributor on Stack Overflow having answered over 400 questions. He is an enthusiastic instructor and dedicates his time to helping students at their desk during exercises to ensure understanding.
Ted demonstrates his deep fluency in Python by developing open source Python libraries and is the creator of dexplo, a suite of data science packages that include bar_chart_race, dexplot, jupyter_to_medium, and dataframe_image.
Ted holds a Master's degree in Statistics from Rice University.
Testimonials
Prerequisites
Build an Interactive Analytics Dashboard with Python assumes you already have a solid understanding of the fundamentals of Python and the Pandas data analysis library. If you do not have these skills, you should acquire them first.
This course covers a wide range of topics from HTML/CSS to executing commands on a Linux server. None of these skills are strictly necessary to have, but will be helpful in making the course easier to complete.
