Washington, DC - NW Conference Center

20 F St NW, Washington, United States, 20001

The venue is situated in the Capitol Hill area on F Street NW, with easy driving access via Massachusetts Avenue and I-395; paid parking is available on-site and in nearby garages. From Ronald Reagan Washington National Airport (DCA), about 5 miles away, a taxi or rideshare via I-395 North typically takes 15–20 minutes. From Dulles International Airport (IAD), approximately 26 miles away, the trip via the Dulles Access Road and I-66/I-395 takes roughly 35–45 minutes. Public transit is extremely convenient with Union Station Metro just one block away (Red Line) and multiple Metrobus routes along F, H, and G Streets NW.
NobleProg Training Place, City Washington, DC - Regus One Franklin Square

Washington, DC - Regus One Franklin Square

1300 I Street NW, Suite 400E, Washington, United States, 20005

The venue sits prominently at One Franklin Square, in downtown Washington, DC, easily reachable by car via Massachusetts Avenue or I‑395 with paid garage parking available in the Franklin Square complex. From Ronald Reagan Washington National Airport (DCA), around 5 miles away, taxi or rideshare via I‑395 typically takes 15–20 minutes. From Dulles International Airport (IAD), approximately 26 miles away, the journey via the Dulles Access Road and I‑66/I‑395 takes about 35–45 minutes. For public transit, McPherson Square Metro Station (Orange, Silver, and Blue lines) is a short two-block walk, and multiple Metrobus routes run along I Street NW, providing convenient access to the venue.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in Washington D.C. (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 Washington D.C. (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 Washington D.C. (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 Washington D.C. (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
Washington, DC - Regus One Franklin Square
$ 6371 (Online)
$ 6371 (Classroom)

Kubeflow Fundamentals

2025-09-01 9:30 am
28 hours
Washington, DC - NW Conference Center
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow on Azure

2025-09-15 9:30 am
28 hours
Washington, DC - Regus One Franklin Square
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow Fundamentals

2025-09-29 9:30 am
28 hours
Washington, DC - NW Conference Center
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow

2025-10-13 9:30 am
35 hours
Washington, DC - Regus One Franklin Square
$ 6757 (Online)
$ 6757 (Classroom)

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Kubeflow Consulting
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