**Workshop tickets are sold separately**

This workshop is a crash course for practitioners who want to leverage fresh data to improve their model performance and/or unlock new business use cases. We'll start with what real-time ML means and when to use real-time ML, with case studies from companies and what they've learned. We'll discuss stages and challenges for companies to move their pipelines towards real-time, with considerations for cost, internal infrastructure, and existing tooling. Real-time ML requires the collaboration of multiple user profiles -- data scientists, data engineers, and ML engineers -- and we'll discuss API decisions that we'll need to consider to enable all these users to productively contribute to real-time ML.