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User-friendly dashboards are a popular, intuitive way for teams to communicate the results of their data analysis. This does not need an expensive platform, and you can create it all in Python. This course teaches you to create dashboards in Python and is perfect for individuals who would like to highlight their analyses in a distributable format while saving the time and expense of becoming experts at front-end programming languages or paying for enterprise software solutions.

This advanced data engineering course focuses on:

  • Plotly-Dash
  • Streamlit
  • Flask

Quick Facts:

Dates: Spring 5/16/2022 – 5/26/2022

Days: Monday – Thursday

Time: 4:00p.m. – 6:30p.m. PT

Format: Online instruction

      Cost: $1,250

      Prerequisites: Python Foundations

      and DS Foundations or equivalent


Meet the Instructor

Dr. Beckner is a GIX faculty member, an instructor for the University of Washington MS in Technology Innovation, a Data Science Advisor for the Pfaendtner Research Group, and partner at MFG Analytic, where he works with manufacturing clients to optimize their production processes using cloud-based tools. He received his Ph.D. in Chemical Engineering Data Science from the University of Washington and his B.S. in Chemical Engineering from the University of Texas at Austin. His consulting work inspired him to help organizations streamline their workflows and increase profit margins by training in-house employees to better understand and use data. Read his full biography here.

Instructor’s Take: Take this course if you would like to distribute your analyses in a dashboard format. Together we will deep dive into the technical aspects of dashboarding as well as the theoretical strategies and best practices for visualization. This course pairs great with Python DevOps or can be taken completely on its own.


I really liked the many concepts introduced, and in particular, loved the stats run-down. I loved the graphics, and I'm really thankful for the sharing of code for both general graphics and statistical visualization.

Darby, Past Participant

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