Are you a Python user who is searching for a way to easily create powerful and flexible web applications for data science and analytics? Have you tried existing Python web application frameworks like Django or Streamlit, but felt that something was missing? Have you wanted to bring the ease of use and flexibility of Shiny for R into your Python workflow? Well, the wait is over. Join us for our inaugural “Shiny for Python” Masterclass, where you can learn from our dashboard experts how to easily create powerful, Python based Shiny web applications!

Note: All our trainings are supported by fully qualified software engineers and interface design experts trained under our partnership with Posit to bring best practice to participants; whatever their background.

Check out our Masterclasses on R Shiny and Automated Reporting with Quarto.

Where
Online Masterclass

When
10–21 February 2025

Price
$2270 NZD
Places are limited, register now to reserve your place.
10% discount for attendees of previous Masterclasses

Why Shiny for Python?

Python is commonly referred to as the ‘second best language for everything’, but don’t let that fool you. Python is an immensely powerful language, with a simple and easy to use syntax, vast amounts of documentation and a rich open-source community supporting an extensive array of packages.

Posit has been hard at work developing the Shiny for Python package and has recently released version 1.0 to the world. With Shiny for Python, you can access all the benefits of Shiny’s customisable framework and simple reactive programming within the comfort of your existing Python environment! You can quickly and easily develop and deploy aesthetically pleasing, interactive web-based dashboards to tell better stories with your data – while also taking advantage of powerful R packages to power your visualisations. You can also customise the look, feel and function of your dashboard to your heart’s content; from one of Shiny’s pre-made layouts or from scratch, using CSS and JavaScript to super-charge your app.

Is this the class for me?

The numbers speak for themselves.

Established in 2018, our Masterclasses have been completed by 150 participants from 78 organisations joining from 18 countries. The training is highly interactive, delivered in small groups, enhanced by an online learning platform with active support provided throughout by our team. 

Here's what our participants say

The R Shiny Masterclass Series was essential for us to set the foundations that led to the development of an interactive report on use of antimicrobial in dairy production in Quebec, Canada. It covered many of the most important Shiny R features and helped us a lot to pick the best approach. We got hooked and we are thus already working on our next app! We feel Shiny is an awesome way to make complex data and fancy epi work digestible and appealing for stakeholders.

Simon Dufour, Université de Montréal

EPI-Interactive’s R Shiny Masterclass is a great introduction to advanced-level concepts in Shiny. I’d recommend it to anyone who feels like they know the basics of building a dashboard in Shiny and want to know, “What’s next?”

Jan-Yves Ruzicka, Ministry of Business, Innovation and Employment (MBIE)

The advanced Shiny masterclass lived up to (even exceeded) our hopes. Colleagues and I found the sessions well structured, not too lengthy, with a good balance between content and breakout sessions, and practically-oriented. Best of all, the exercises to do between sessions were well designed for us to hone our skills. Managing it all on RStudio Cloud was a genius move.

Paddy Tobias, Social Research Centre Australia

Course instructors

Nick Snellgrove
Nick Snellgrove
Tech Lead

Passionate about building fit-for purpose software for our clients, Nick is our go to problem solver. Along with being fluent in R and R Shiny development, he has a particular passion for spatial data visualisations, performance tuning of Shiny apps, and User Experience (UX) development.

Ben Rhodes
Ben Rhodes
Full-Stack Developer

Ben is a resourceful multi-talented developer who is especially skilled when it comes to the back-end of any Shiny project. His awesome background in cloud infrastructure and extensive IT knowledge make him very effective at designing robust Shiny applications with many moving parts.

Poppy Schlaadt
Poppy Schlaadt
Junior Developer

Poppy brings to the team a passion for creating dynamic digital solutions that meet practical needs and address computational complexities. She is especially talented with rapid development of feature rich Shiny interfaces and visualisations in record time.

Schedule

Session start times

North America

Los Angeles (PDT) | 12pm

  1. 10 February 2025
  2. 11 February 2025
  3. 13 February 2025
  4. 17 February 2025
  5. 18 February 2025
  6. 20 February 2025
     

Toronto (EDT) | 3pm

  1. 10 February 2025
  2. 11 February 2025
  3. 13 February 2025
  4. 17 February 2025
  5. 18 February 2025
  6. 20 February 2025

Europe

London (BST) | 8pm

  1. 10 February 2025
  2. 11 February 2025
  3. 13 February 2025
  4. 17 February 2025
  5. 18 February 2025
  6. 20 February 2025

Paris (CEST) | 9pm

  1. 10 February 2025
  2. 11 February 2025
  3. 13 February 2025
  4. 17 February 2025
  5. 18 February 2025
  6. 20 February 2025

Oceania

Sydney (AEST) | 7am

  1. 11 February 2025
  2. 12 February 2025
  3. 14 February 2025
  4. 18 February 2025
  5. 19 February 2025
  6. 21 February 2025

New Zealand (NZDT) | 9am

  1. 11 February 2025
  2. 12 February 2025
  3. 14 February 2025
  4. 18 February 2025
  5. 19 February 2025
  6. 21 February 2025 

Each session is 90 min long (online Zoom tutorial). We also recommend putting some time aside in-between the sessions to work on assignments and to practice in your own time, ideally at least one hour.

Learning objectives

  • Learn the anatomy of a simple Shiny for Python application
  • Understand the workflow of developing a Shiny application
  • Learn to create a basic Shiny app interface
  • Understand user inputs, and simple plot outputs in Shiny
  • Understand reactivity and how it can be used in a Shiny app
  • Perform basic data transformations reactively in a Shiny app
  • Create static and interactive plot outputs in a Shiny app
  • Learn how to debug your Shiny for Python application if things go wrong
  • Publish your Shiny for Python application to Shinyapps.io