MLOps Platforming Workshop

2 hours

As organizations aspire to increase their overall level of data maturity — capable of managing and extracting insights from much larger datasets — another challenge has emerged. Companies are now looking for ways to push machine learning (ML) models out to production in a standardized and consistent fashion, enabling data science teams to develop more models and deliver more business insights. The MLOps Platforming Workshop is an interactive session designed to explore your operational readiness to deploy and scale an MLOps platform for ML productionalization. 

What to Expect

During an MLOps Platforming Workshop, WWT experts will share insights and use cases that will help drive actionable outcomes around how to successfully implement the MLOps methodology within an organization. The workshop includes the following:

  • Overview of what MLOps is and the benefits it can provide
  • Review current data science model training and deployment practices
  • Discuss the current issues related to the ML operations tools and platform
  • Deep dive on current bottlenecks and challenges deploying ML models at scale
  • Discussion of trade-offs between the platforms available

Goals & Objectives

The MLOps Platform Workshop will explore the advantages and considerations for adoption of MLOps best practices for your organization. You will increase your understanding of the processes and technologies required to enable your data science teams to productionalize machine learning at scale. 

WWT experts will engage with workshop participants to develop specific use cases, understand available solutions and assess the differences and specific benefits of each.

What is a workshop? A workshop is a working session in which technology decision makers, architects, engineers and line of business representation meet with WWT subject matter experts, engineers, program/process management and sales teams to evaluate or compare how specific strategies and technologies could be deployed in your organization. These are paid engagements with a defined outcome and deliverable, e.g., action plan, high-level architectural design, proposal or quote for project implementation. They take place in-person or via video conference and last from 2 hours to 5 days.

Who should attend? (this list is non-exhaustive)

  • Chief Data Scientist
  • Chief Technology Officer


From this workshop, attendees will come away with more than a better understanding of their internal use cases, pain points and available paths forward. In addition to these advantages, attendees will be able to better understand: 

  • the advantages associated with MLOps;
  • the challenges that can impede a successful ML development environment and how to overcome them; and
  • the platforming considerations to be aware of when conducting ML initiatives.
What's Next?
Learn more about Data Analytics & AI, stay up-to-date with the industry and the new technology we have at WWT.