Pydata Bradford - March Meetup

AI Beyond the Buzz: Real Applications and Impact Across Industries
AI is everywhere right now but beyond the headlines and hype, how is it actually being used in real industries? Join us at PyData Bradford for an evening of practical insights, real-world experiences, and honest conversations about how AI is transforming different sectors. This event will feature two engaging sessions designed for anyone working in data, AI, software engineering, research, or technology.

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Session 1: Panel Discussion
AI Beyond the Buzz: Real Applications and Impact Across Industries
Our panel brings together professionals from recruitment, software engineering, legal tech, and data science to discuss how AI is being used in practice across industries.
We’ll explore:

• Real-world AI applications in different sectors
• What it actually takes to implement AI in organisations
• Challenges teams face when adopting AI
• Ethical and practical considerations
• What the future of AI adoption might look like

This will be an interactive discussion, so come prepared with questions.

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Session 2: Talk
“But, it worked on my laptop!”
Abstract
Imagine two researchers (A and B) collaborating to create an analysis workflow. Researcher A writes a data preprocessing script on their laptop and successfully generates the expected output. They share the script with Researcher B, who tries to run it on their own machine using the same dataset.
Instead of working, Researcher B encounters errors like “module not found.”
Researcher A is surprised and says:
“But, it worked on my laptop!”
This situation highlights a common issue in research and data science: non-reproducible workflows.
In this talk, we will explore practical strategies to avoid these problems and discuss software engineering practices that make research code easier to reproduce, share, and maintain.
Topics include:

• Reproducible research workflows
• Managing dependencies
• Structuring research code for collaboration
• Practical tools and good software engineering practices

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## Who Should Attend?

This event is ideal for:

• Data scientists
• AI and machine learning practitioners
• Researchers
• Software engineers
• Anyone interested in practical AI and data science

Basic familiarity with programming languages such as Python or R will be helpful for the talk.