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Creating Machine Learning Apps in Python using Dash and Plotly

In this course, you learn how to create Machine Learning Apps in Python using Dash and Plotly. It will go live in September 2020.

About This Course

IIn this course, participants learn to create interactive dashboards with Python to make their data science analysis available to costumes or colleagues. More specifically, they will learn to use the Python libraries Dash and Plotly. We will guide them to create their first own Dash apps purely by using Python code but also provide some insight to the functionality of the framework which automatically creates html and java script code. For our Dash apps we will use climatological data provided by APIs by NASA. These data are daily updated. We show how to connect the app to these live data and how to deploy it, i.e. to share the Dash app and give access to costumes or colleagues.

The course provides a sound mix of both theoretical and technical insights , as well as practical implementation details. These are illustrated by several real-life case studies and examples. Throughout the course, the instructors also extensively report upon their research and industry experience.

The course features more than 4 hours of video lectures, more than 100 multiple choice questions, and various references to background literature. A certificate signed by the instructors is provided upon successful completion.

See TBC to get a free teaser of the course contents.

We can also come and teach this course on-site in classroom format. If interested, please mail us at:


The enrollment fee for this course is EUR 250 (VAT excl.) per participant. Payments are securely handled by PayPal. If you are a company in the European Union, then we can apply VAT reverse charge. For this, please mail your VAT number to Part of our course revenue is used towards funding organizations involvement in protecting and cleaning our oceans. See our about page to learn more about our mission statement.


Before subscribing to this course, you should have a basic understanding of descriptive statistics (e.g., mean, median, standard deviation, histograms, scatter plots, etc.) and inference (e.g., confidence intervals, hypothesis testing). You should also have followed and completed our Machine Learning Essentials course.

Course Outline

  • Introduction
    • Introduction to Dash
    • Behind the scenes (java script, css, html and Flask server)
    • Introduction to API data: NASA POWER
    • Outlook dashboards
    • Quiz
  • Plotly
    • Getting started with Plotly
    • Basic Charts (scatter plots, line charts, box plots, histograms, bar charts)
    • Visualization of API data (Time series of average global temperature, wind speed and air pressure)
    • Quiz
  • Static apps with Dash
    • Getting started with Dash
    • Dash Layouts
    • Dash HTML Components
    • Dash core components
    • Quiz
  • Dynamic apps with Dash
    • Introduction to callbacks
    • Inputs and outputs
    • Advanced callbacks
    • Online data: Live updates
    • Quiz
  • Deployment
    • Flask in production
    • Hosted by cloud solutions
    • Self-hosted options
    • Quiz
  • Quiz

Course Staff

Dr. Irene Ortner

Dr. Irene Ortner

Dr. Leonhard Horstmeyer

Dr. Leonhard Horstmeyer