Today, data teams are often divided between those who code in Python and those who rely on visual workflows. For many Python developers, data science projects often start strong, but scaling and collaboration can quickly become a challenge. Scripts can grow too complex, debugging can take a lot of time, and sharing the models with non-coders can be tedious.
This separation between Python developers and the rest of the data team slows collaboration, makes automation harder, and creates silos between data engineers, analysts, and scientists.
Join our webinar on October 29 to see how to remove that barrier and make the work of Python developers available to less technical team members who don’t code. By empowering business users with EasyMorph’s no-code workflows that can embed Python scripts, Python developers provide users with access to machine learning, predictive analytics, and data science, all under one roof.
Whether you already work with EasyMorph or with Python, this session will show how both worlds can finally come together for faster, clearer, and more collaborative data work.
Register NowWhat’s Covered in the Webinar?
Matt Fryer
Technology Evangelist @ EasyMorph
Topic 1: Hands-On with Python and EasyMorph
Matt will take you step-by-step through using Python in real EasyMorph workflows, showing practical data science and predictive analytics examples. You’ll discover:
- How to get started with Python inside EasyMorph using the new “Call Python” action.
- The difference between Call Python and Run Program actions.
- How the new EasyMorph Python library works, including converting datasets to and from Pandas DataFrames.
- How to perform your first Python-powered data science analysis directly within a visual workflow.
- Real-world examples like scoring datasets, training models, and enriching data with AI predictions.
At the end, Matt will explore additional use cases, showing how to integrate Python scripts with your existing workflows.
Dmitry Gudkov
Founder @ EasyMorph
Topic 2: The Future of Python in EasyMorph
Dmitry will provide an overview of EasyMorph’s evolution and vision for uniting data engineering and data science in one platform. You’ll learn:
- How EasyMorph’s visual workflows simplify data preparation for AI and Machine Learning.
- How the new Python integration creates a shared environment for technical and non-technical users.
- Why this marks a major step forward for collaborative data science, democratizing Python’s power across entire teams.
Together, these advances reveal how EasyMorph is shaping the future of data collaboration, where Python developers and analysts can finally work side by side in one unified environment.
Live Q&A – 10 Minutes
At the end of the session, we’ll open the field for questions. Bring your questions on Python, data automation, and how to build better collaboration between your technical and non-technical teams.
Who Should Attend?
This session is built for:
- Existing EasyMorph users who want to start using Python inside their current workflows.
- Python developers and data scientists looking to simplify and visualize their data prep for ML and predictive analytics.
- Data analysts and engineer who want to collaborate in one environment instead of juggling multiple tools.
You don’t need deep coding experience, just curiosity and a desire to see how EasyMorph and Python work better together.
Why EasyMorph?
EEasyMorph was designed to make data automation accessible for everyone. Now, with our Python integration, EasyMorph is also a powerful environment for data science, machine learning, and predictive analytics. Visual users gain Python power while Python users gain workflow visibility. The result is faster data preparation, easier collaboration, and fewer silos.
Register NowBonus: All registrants receive access to the replay and a downloadable quick-start guide for integrating Python in EasyMorph.
Space is limited, save your seat today.
