Red Hat OpenShift / Open Data Science Conference (ODSC) Europe 2021

Smart Cities are complex and challenging environments. They generate an overwhelming amount of data that you have to ingest, transfer, prepare and store even before thinking of analyzing them or training a model. In this presentation based on a fictitious but concrete scenario, in the city of London, we will see how you can leverage different data engineering patterns to create a full edge-to-core data pipeline. All of these: Computer Vision, Kafka, Object Storage, Data aggregation, Real-time and Batch analysis, in a fully cloud-native containerized environment, are some of the technologies we will explore and see working live.

After this session, you should get a better understanding on how to get your models in production, how to automate some data engineering workflows, and how to build a resilient production-grade data workflow infrastructure.

Turkcell is a leading converged telecommunication and technology services provider. Operating within Turkey and internationally, Turkcell currently serves close to 48 million customers with a wide range of communications and digital services offerings. AI has been integral to Turkcell’s strategic vision, covering areas such as computer vision, natural language processing and intelligent automation to help transform customer experiences, drive operational efficiencies and bring a greater diversity of consumer and business innovations to market faster.

In this keynote, Turkcell and Red Hat will provide an overview of Turkcell’s AI use cases, and how they went about building a flexible, secure cloud platform to accelerate AI development, and associated delivery of intelligent applications. Technologies such as Red Hat OpenShift, JupyterLab, NVIDIA GPUs helped provide the much needed execution agility for Turkcell’s AI strategy.

You will also hear lessons learned across people, process, and technology transformation to help operationalize Turkcell’s AI strategy, and how these lessons have helped enhance work for data scientists, software developers, DevOps, and IT operations teams.

Data science projects can fail before ever being realized. Integrating data science into your application development workflow and tooling from the beginning can greatly improve chances of success. In this demo, we show how a data scientist uses Red Hat OpenShift Data Science, along with partners and open source software, to develop a model and integrate it as part of a heterogeneous application.

In this session, learn how Red Hat, the world’s leading provider of enterprise open source solutions, in partnership with C3.ai, is helping customers develop scalable intelligent applications leveraging AI and machine learning. We’ll walk you through a practical example of digitizing engineering diagrams to enable machine learning-based predictive maintenance. Engineering diagrams are a vital data source for industrial facilities, depicting the configuration and properties of equipment, sensors, and process flow. In this session we will:

- Show how to leverage containers and Kubernetes to provide agility, flexibility, and scalability to enterprise AI application development
- A computer vision pipeline using state-of-the-art deep learning and graph search techniques to parse diagrams and generate structured asset hierarchies
- Show how these hierarchies allow operators to represent their assets digitally and enable intelligent applications

If you are like me, the first time you heard of 'Managed Services' you scratched your head and said 'What are Managed Services? What do they have to do with Model Delivery? Where do I go for Managed Services? And of course, my favorite question with any new technology, are they easy to use?

Join me for a session in which we will learn what managed services are and how they are being more frequently used in hybrid cloud platforms to enhance and help with the Model Delivery process. We will finish the session, by taking a quick look at what managed services are available in the new Red Hat OpenShift Data Science platform.

Let's help you understand what Managed Services are so that you can 'manage' your way into delivering your models faster and more easily!