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Starts 6 July 2025 13:59

Ends 6 July 2025

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Microsoft SQL Server Machine Learning Workloads on Red Hat Enterprise Linux and Red Hat OpenShift

Join us to explore the integration of Microsoft SQL Server with Red Hat Enterprise Linux and OpenShift, enabling accelerated machine learning pipelines. This session offers insight into using in-database machine learning techniques and the benefits of containerization for efficient model production and deployment. Optimize your machine le.
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PASS Data Community Summit

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Overview

Join us to explore the integration of Microsoft SQL Server with Red Hat Enterprise Linux and OpenShift, enabling accelerated machine learning pipelines. This session offers insight into using in-database machine learning techniques and the benefits of containerization for efficient model production and deployment.

Optimize your machine learning workflows by leveraging SQL Server's capabilities on robust platforms like Red Hat.

Gain practical knowledge and skills to streamline your data science processes, ensuring quicker, more reliable outcomes.

Categories:

Artificial Intelligence Courses, Conference Talks

Syllabus

  • Introduction to Microsoft SQL Server on Red Hat
  • Overview of SQL Server capabilities
    Introduction to Red Hat Enterprise Linux and OpenShift
    Understanding machine learning workloads in SQL Server
  • Setting Up SQL Server on Red Hat Enterprise Linux
  • Installation and configuration of SQL Server on RHEL
    Essential RHEL commands for managing SQL Server
    Performance tuning and optimization in RHEL
  • In-Database Machine Learning with SQL Server
  • Overview of SQL Server Machine Learning Services
    Implementing R and Python scripts in SQL Server
    Data preparation and transformation using SQL Server
  • Building and Optimizing ML Pipelines
  • Designing efficient machine learning workflows
    Model training and evaluation within SQL Server
    Leveraging SQL Server for data ingestion and processing
  • Containerizing SQL Server for Machine Learning
  • Introduction to containers and container orchestration
    Deploying SQL Server on OpenShift
    Best practices for containerized machine learning workloads
  • Deploying Machine Learning Models on OpenShift
  • Continuous integration and deployment for ML models
    Creating and managing OpenShift deployments for ML solutions
    Monitoring and scaling ML applications on OpenShift
  • Security and Maintenance
  • Implementing security best practices for SQL Server and OpenShift
    Regular maintenance tasks for databases and containers
    Backup and recovery strategies for SQL Server on Linux
  • Case Studies and Real-World Applications
  • Exploring real-world scenarios using SQL Server ML workloads
    Success stories and industry applications
    Lessons learned and future trends in SQL Server ML on RHEL
  • Final Project
  • Design, implement, and deploy a complete ML pipeline using SQL Server on RHEL and OpenShift
    Presentation and peer review of final projects

Subjects

Conference Talks