MN, Minneapolis - Fifth Street Towers

100 S 5th St, 19th Floor, Minneapolis, United States, 55402

The venue is located in the heart of downtown Minneapolis at Fifth Street Towers, easily accessed by car via I‑94 or I‑35W with exits to S 5th St; paid underground parking is available in the building garage. From Minneapolis–Saint Paul International Airport (MSP), take I‑494 North to I‑35W North, then exit at 5th Street—taxi or rideshare takes around 20 minutes. Public transit users can arrive via the METRO light rail to Nicollet Mall Station or by several bus routes that stop on 5th Street, with the entrance a brief walk from public transit.

Eagan, MN - Grand Oak I

860 Blue Gentian Rd, Ste 200, Eagen, United States, 55121

The venue is located in the Grand Oak Business Park at 860 Blue Gentian Road, easily accessed by car via I‑494 and Highway 55; ample on-site parking makes arrival simple. From Minneapolis–Saint Paul International Airport (MSP), it’s about a 5‑minute drive—take I‑494 East and exit at Blue Gentian Road. Public transit users can take Metro Transit bus routes to a stop near Blue Gentian Road and walk a few minutes from there.

Explore Our Courses

Kubeflow

 35 Hours

This instructor-led, live training in Minnesota (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 Minnesota (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 Minnesota (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.
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Kubeflow on Azure

 28 Hours

This instructor-led, live training in Minnesota (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
MN, Minneapolis - Fifth Street Towers
$ 6371 (Online)
$ 8371 (Classroom)

Kubeflow Fundamentals

2025-09-01 9:30 am
28 hours
MN, Minneapolis - Fifth Street Towers
$ 5405 (Online)
$ 7405 (Classroom)

Kubeflow on Azure

2025-09-15 9:30 am
28 hours
MN, Minneapolis - Fifth Street Towers
$ 5405 (Online)
$ 7405 (Classroom)

Kubeflow Fundamentals

2025-09-29 9:30 am
28 hours
MN, Minneapolis - Fifth Street Towers
$ 5405 (Online)
$ 7405 (Classroom)

Kubeflow

2025-10-13 9:30 am
35 hours
MN, Minneapolis - Fifth Street Towers
$ 6757 (Online)
$ 9257 (Classroom)

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