Sheffield

The Chimney House, 4 Kelham Island, Sheffield, united kingdom, S3 8RY

The Chimney House is a creative and innovative space in the centre of Sheffield – the biggest feedback we receive from companies that use us is that they noticeably observe higher levels of performance and interaction from teams and individuals. The building is formed on the ethos of the truest form of recycling – 85% of furnitures, fittings and décor has been created from reclaim and salvage and matched with a ultra modern outlook. We host meetings, trainings, brainstorming sessions, workshops, away days and conferences as well as product launches, interviews, filming and photoshoots on a daily basis. Light, airy with plenty of table space, multiple power sources, hidden screen, wireless projector, state of the art audio system and full building high speed wi-fi. Need to break out? We can help, with a choice of 2 additional rooms for hire. We're famed for our lunches that are brim full of Yorkshire fresh produce. Sourced from the 7 hills of Sheffield and supporting local and independent makers and bakers, our lunches are tip top tasty with cake to die for! There are multiple car parks within a few minutes walk. We can provide a handy 'How to Guide' to recommend the easiest way to arrive by road, rail, bicycle, foot and tram. We are also home to Supper Society, a secret dining society that meets sporadically, hosted by guest chefs. The only time an individual seat at The Chimney House table can be acquired.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in Sheffield (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of this training, participants will be able to:

  • Install and configure Kubeflow on premise and in the cloud using AWS EKS (Elastic Kubernetes Service).
  • Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
  • Run entire machine learning pipelines on diverse architectures and cloud environments.
  • Using Kubeflow to spawn and manage Jupyter notebooks.
  • Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Read more...

Kubeflow Fundamentals

 28 Hours

This instructor-led, live training in Sheffield (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of this training, participants will be able to:

  • Install and configure Kubeflow on premise and in the cloud.
  • Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
  • Run entire machine learning pipelines on diverse architectures and cloud environments.
  • Using Kubeflow to spawn and manage Jupyter notebooks.
  • Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Read more...

Kubeflow on AWS

 28 Hours

This instructor-led, live training in Sheffield (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to an AWS EC2 server.

By the end of this training, participants will be able to:

  • Install and configure Kubernetes, Kubeflow and other needed software on AWS.
  • Use EKS (Elastic Kubernetes Service) to simplify the work of initializing a Kubernetes cluster on AWS.
  • Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
  • Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
  • Leverage other AWS managed services to extend an ML application.
Read more...

Kubeflow on Azure

 28 Hours

This instructor-led, live training in Sheffield (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to Azure cloud.

By the end of this training, participants will be able to:

  • Install and configure Kubernetes, Kubeflow and other needed software on Azure.
  • Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
  • Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
  • Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
  • Leverage other AWS managed services to extend an ML application.
Read more...

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Testimonials (1)

I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.

Guillaume Gautier - OLEA MEDICAL | Improved diagnosis for life TM

Course - Kubeflow

Provisional Upcoming Courses (Contact Us For More Information)

Kubeflow

2025-08-11 09:30
35 hours
Sheffield

Kubeflow on AWS

2025-09-08 09:30
28 hours
Sheffield

Kubeflow

2025-09-22 09:30
35 hours
Sheffield

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Consulting/Staffing

Kubeflow Consulting
Kubeflow Staffing
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