A data scientist’s perspective of the common data and business process challenges that can hinder the development of AI and machine learning projects.

About the event

Giving a realistic account of the challenges of data science delivery and how to overcome them, this talk will explain how AI and machine learning projects differ in their design to typical engineering projects, and practical solutions to make the most of a proof of concept. Maybe you’re a business leader wondering why you’ve still not seen a finished AI product, a delivery manager confused about why data exploration is spilling into another sprint, or even a data scientist looking for group therapy – this is an honest account of problems you can see along the way and pragmatic steps you can take to ease the pain. It also raises the question: is a complex AI product going to solve the business problem, or is there a more simple solution to try first?

Further information

Speaker

• Suze Hawkins is a Lead Data Scientist at Hippo. Applying knowledge from an academic career in epidemiology, she has several years experience in various sectors, including creating data science operating models to help organisations on their journey to data maturity.

Target audience

•  Anyone wanting to embark on an AI journey. [Data scientists, data analysts, data engineers, business analysts, project managers].