Bangor, Maine

700 Main St, Suite 3, Bangor, United States, 04401

This venue is conveniently situated near downtown Bangor, with easy access by car via I‑95 and US‑2. There is nearby public parking garages and metered on-street parking. From Bangor International Airport (BGR), about 8 miles northwest, a taxi or rideshare typically takes around 15 minutes via ME‑15 and I‑95 South. The public transit service, BAT Commuter, operates bus routes that run along Main Street with stops just a short walk from the building.
NobleProg Training Place, City Portland, ME - Regus at Congress Street

Portland, ME - Regus at Congress Street

400 Congress St, Suite 300, Portland, United States, 04101

The venue is located in Portland’s central business district on Congress Street, with easy car access via I‑95, I‑295, and US‑1, and several public parking garages nearby. From Portland International Jetport (PWM), roughly 3 km away, a taxi or rideshare via Congress Street takes around 10 minutes. Public transportation is convenient, with the Congress St & Elm St bus stop at the building entrance providing multiple Greater Portland Metro bus routes.

Explore Our Courses

Kubeflow

 35 Hours

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

Upcoming Courses

Kubeflow on AWS

2025-08-18 9:30 am
28 hours
Bangor, Maine
$ 6371 (Online)
$ 6371 (Classroom)

Kubeflow Fundamentals

2025-09-01 9:30 am
28 hours
Bangor, Maine
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow on Azure

2025-09-15 9:30 am
28 hours
Bangor, Maine
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow Fundamentals

2025-09-29 9:30 am
28 hours
Bangor, Maine
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow

2025-10-13 9:30 am
35 hours
Bangor, Maine
$ 6757 (Online)
$ 6757 (Classroom)

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Kubeflow Consulting
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