OVERVIEW
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 Verta.ai and Superset
- Automating and secure model deployment including MLOPs using Jenkins
- 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
While coding / development skills aren’t required, a familiarity with coding will be advantageous.
Questions? Please contact Rebecca Innes, rinnes@redhat.com.
