Plymouth

Regus Drake Circus, Unit MSU9A, Level 1, Plymouth, united kingdom, PL1 1EA

Business travellers now have somewhere to work and meet while on the go – walk-in workspace at Drake Circus shopping centre in Plymouth. Our business lounge features flexible workspace and desks along with meeting rooms to rent by the day, half-day or hour. Work smart and meet your clients in a professional environment. A virtual office service is also available. It’s easy to access by car and there’s plentiful parking at this site close to Plymouth University and the City Museum. The railway station is just 10 minutes away on foot. • Fully-equipped meeting rooms • Fully equipped private day offices • Free high speed WiFi and refreshments • Business class facilities – print, scan and copy documents • Plentiful parking • Walk in business lounge with flexible workspace to work productively • Virtual offices – mail handling, business address & telephone answering How to find us: We are located on Car Park Level 1/Food Court, next to The Entertainer Toy Shop.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in Plymouth (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.
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Kubeflow Fundamentals

 28 Hours

This instructor-led, live training in Plymouth (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 Plymouth (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 Plymouth (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
Plymouth

Kubeflow on AWS

2025-09-08 09:30
28 hours
Plymouth

Kubeflow

2025-09-22 09:30
35 hours
Plymouth

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Consulting/Staffing

Kubeflow Consulting
Kubeflow Staffing
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