The Path Forward on Scaling AI and Data Science Part 2: Retire technical debt and open up data scien

When:  Feb 2, 2021 from 9:00 AM to 10:15 AM (PT)

The Path Forward on Scaling AI and Data Science

Online Event Series on Accelerating Digital Transformation and AI-Powered Innovation


AI and hybrid cloud are crucial technologies that help organizations navigate a different normal. Business leaders are adopting new ways of predicting and optimizing outcomes and scaling up AI-powered innovation. To identify and act on new insights and patterns across the evolving business landscape, they are rapidly tackling challenges in data, models, architectures, talent, and processes. How do we unify the tools and govern the AI lifecycle?  In what ways can we ensure trust and compliance across all data, AI and open source assets? In this online event series, IBM and IBM business partners will discuss AI-powered solutions, best practices and lessons learned to speed time to production, drive productivity and growth, and manage risks and compliance on a modern information architecture on IBM Cloud Pak for Data.  

Register now and explore your path forward for digitally re-inventing and future proofing your data and AI strategy.

Part 2:  Retire technical debt and open up data science for all 

This second session will explore the topic of replatforming your legacy tooling to be ready for modern data science and AI. To succeed in AI, in addition to implementing new capabilities, you need to retire technical debt and bring all contributors in a unified environment. We will discuss:

  • Key considerations when you decide to replatform
  • Architecting for the era of AI - talent, technology, process and business
  • Diversity of tools for diverse talent  - visual data science, programmatic data science and other tooling
  • How to get started with Watson Studio Premium for IBM Cloud Pak for Data


Michael Gonzales, PhD, Chief Data Scientist, Prolifics

John Radi, Global Sales Leader, Prolifics

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