The Path Forward on Scaling AI and Data Science Part 5: AI engineering: Pragmatic ways to build your ModelOps practice

Part 5: AI engineering: Pragmatic ways to build your ModelOps practice 

The fifth session will cover the topic of ModelOps and AI engineering.  There is a spectrum of technical disciplines that AI and data science teams must consider in operationalizing AI, including ModelOps, DevOps and DataOps.  

• What is AI engineering and why does it matters
• Typical pitfalls that organizations face in operationalizing AI
• ModelOps patterns and options
• Advancements in tools, organizational approaches and processes

Speakers:

Darrell Reimer, Distinguished Engineer, IBM Research

Julianna Delua, Data Science and AI SME, IBM Data and AI