Accelerate your AI/ML lifecycle with enterprise Kubernetes

Join Red Hat's AI/ML experts as they guide you through the AI/ML Lifecycle - from Data Engineering, Data Science, and ML-Ops, that will see your models running in production. You will experience how Red Hat’s enterprise Kubernetes platform, OpenShift, solves problems that often reduce the business value of AI/ML including:

• How to produce high quality data for training AI models
• Self-service tool provisioning - radically improving productivity
• Kubernetes scheduling improving hardware utilisation
• Elimination of silos - and enabling rapid work handoff between parties
• Safe, easy and fast movement of models to production for inference

In this workshop, you will create workflows and get hands-on with:

• Self Service of data engineering and data science focused tools including Apache Kafka, Apache Spark, Jupyter Notebooks
• Collaboration and workflow handoff tools such as shared S3 object storage and model repositories and visualization tools such as ML Flow and Superset
• Automating and secure model deployment including MLOPs using Airflow
• Inferencing and model serving tools including Seldon, enabling simple model consumption by intelligent applications over RESTful interfaces.

Who should attend?

• Managers/Heads of - Data Engineers, Data Scientists and Developers
• Data Engineers, Data Scientists and Developers
• DevOps and ML OPs professionals

While coding / development skills aren’t required, a familiarity with coding will be advantageous.

Questions? Please contact Chris Bowden, chbowden@redhat.com.