NobleProg Training Place, City Allentown, PA – Grand Plaza

Allentown, PA – Grand Plaza

835 Hamilton St, Allentown, United States, 18101

The venue is located in the iconic Grand Plaza building in downtown Allentown, accessible by car via I‑78 or US‑22, with nearby public parking lots and street spaces. From Lehigh Valley International Airport (ABE), about 6 miles north, a taxi or rideshare takes approximately 10–15 minutes via Airport Road and Hamilton Street. Public transit users can take LANta bus routes that stop directly on Hamilton Street, with the center just steps from the bus stop, offering convenient access without a vehicle.

Harrisburg, PA – Regus at Campus Square

1426 North 3rd Street, 4th Floor, Harrisburg, United States, 17102

The venue is situated in the modern LEED Gold–certified Campus Square building at 1426 N 3rd Street in Midtown Harrisburg, easily reachable by car via I‑83 or Route 230, with ample on-site parking and nearby municipal garages. From Harrisburg International Airport (MDT), about 12 miles southwest, a taxi or rideshare typically takes 15–20 minutes via PA‑283 West and I‑83 North. Public transit is convenient: several Capital Area Transit buses stop within a block, and the building is within walking distance of major routes and complemented by Midtown’s walkable environment and local amenities.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in Pennsylvania (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 Pennsylvania (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 Pennsylvania (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 Pennsylvania (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
Allentown, PA – Grand Plaza
$ 6371 (Online)
$ 6371 (Classroom)

Kubeflow Fundamentals

2025-09-01 9:30 am
28 hours
Allentown, PA – Grand Plaza
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow on Azure

2025-09-15 9:30 am
28 hours
Allentown, PA – Grand Plaza
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow Fundamentals

2025-09-29 9:30 am
28 hours
Allentown, PA – Grand Plaza
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow

2025-10-13 9:30 am
35 hours
Allentown, PA – Grand Plaza
$ 6757 (Online)
$ 6757 (Classroom)

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Kubeflow Consulting
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