NobleProg Training Place, City Sioux Falls, SD

Sioux Falls, SD

100 E 6th St, Sioux Falls, United States, 57104

The venue is located in the heart of downtown Sioux Falls at 100 East 6th Street in the historic Milwaukee Freight Depot (“The Depot”), easily accessible by car via I‑229 with exits to Phillips or Minnesota Avenue, with both on‑site and nearby public parking available. From Sioux Falls Regional Airport (FSD), head west on SD‑42, then north on I‑229 and exit at Phillips Avenue; the taxi or rideshare trip typically takes about 10 minutes. Public transit users can take Sioux Area Metro buses along Phillips or East 6th Street, followed by a brief walk into a vibrant, pedestrian‑friendly space.

Pierre, South Dakota

808 W Sioux Ave, Pierre, United States, 57501

The ClubHouse Hotel & Suites is located just east of downtown Pierre at 1600 East Highway 14, easily accessible by car via US‑83/US‑14 and offers free on-site parking. From Pierre Regional Airport (PIR), take US‑83 South to East Highway 14—taxi or rideshare takes approximately 5 minutes. Public transit users can catch River Cities Transit to stops on East Hwy 14, followed by a short walk to the hotel entrance.
NobleProg Training Place, City Sioux Falls, SD - Regus - CNA Building

Sioux Falls, SD - Regus - CNA Building

101 S Reid St, Suite 307, Sioux Falls, United States, 57103

The venue is located in the heart of downtown Sioux Falls at 101 South Reid Street in the LEED-certified CNA Building, which offers convenient access via I‑229 with exits to Reid or Phillips Avenue. On-site and nearby public garages provide ample parking. From Sioux Falls Regional Airport (FSD), it’s a 7‑minute drive south via SD‑42; taxi or rideshare typically takes about 10 minutes. Public transit users can take Sioux Area Metro buses along Phillips or Reid Street with stops directly outside the building.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in South Dakota (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 South Dakota (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 South Dakota (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 South Dakota (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
Sioux Falls, SD
$ 6371 (Online)
$ 6371 (Classroom)

Kubeflow Fundamentals

2025-09-01 9:30 am
28 hours
Sioux Falls, SD
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow on Azure

2025-09-15 9:30 am
28 hours
Sioux Falls, SD
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow Fundamentals

2025-09-29 9:30 am
28 hours
Sioux Falls, SD
$ 5405 (Online)
$ 5405 (Classroom)

Kubeflow

2025-10-13 9:30 am
35 hours
Sioux Falls, SD
$ 6757 (Online)
$ 6757 (Classroom)

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