NobleProg Training Place, City Wichita, KS - Regus - Grand Hotel at Union Station

Wichita, KS - Regus - Grand Hotel at Union Station

801 E Douglas Ave, 2nd Floor, Wichita, United States, 67202

The venue is located in the heart of downtown Wichita at Union Station, accessible by car via I‑135 with exits to Douglas Avenue, and includes secure on-site parking. From Wichita Dwight D. Eisenhower National Airport (ICT), take I‑235 East to I‑135 South, exit at Douglas Avenue; taxi or rideshare typically takes about 15 minutes. Public transit users can take Wichita Transit bus routes that stop near Broadway and Douglas, followed by a short walk to the station in a pedestrian-friendly area.

Overland Park, KS - Commerce Plaza

7300 West 110th St, Overland Park, United States, 66210

Commerce Plaza is easily accessible by car via Interstate 435 and local roads such as Metcalf and College Boulevards, with complimentary open parking and nearby garages. Travelers arriving from Kansas City International Airport (MCI) will find the venue approximately 38 miles northeast—a 35 to 45‑minute drive via I‑435. Public transit riders can use Johnson County Transit services, with bus stops located just steps away from the building. Numerous hotels, restaurants, and shopping destinations are all within walking distance, ensuring convenience for attendees
NobleProg Training Place, City Kansas City, KS - The Stables KCK / CABA

Kansas City, KS - The Stables KCK / CABA

1303 Central Ave, Kansas City, United States, 66102

The venue is centrally located in the heart of Kansas City, Kansas, at 1303 Central Avenue, easily accessible by car via I‑70 or I‑35 with exits to Central Avenue; ample free street parking is available along Central Avenue and 13th Street. From Kansas City International Airport (MCI), take I‑70 East to the Central Avenue exit—taxi or rideshare takes about 20 minutes. Public transit users benefit from local bus routes along Central Avenue, with stops just steps away from the entrance in this pedestrian-friendly corridor.
NobleProg Training Place, City Topeka, KS - Omni Circle

Topeka, KS - Omni Circle

1301 SW Topeka Blvd, Topeka, United States, 66612

Omni Circle is centrally located on SW Topeka Boulevard, easily accessible by car with ample public parking nearby in surface lots. Visitors from Forbes Field (Topeka Regional Airport, FOE) can reach the venue in about 10 minutes via SW McAlister Road. Public transport users can take Topeka Metro’s Route 17, which has stops near SW Topeka Boulevard, offering straightforward access for local attendees.

Subcategories (2)

Kubeflow

Kubeflow
MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours

This instructor-led, live training in Kansas (online or onsite) is aimed at advanced-level AI engineers and data scientists with intermediate-to-advanced experience who wish to enhance DeepSeek model performance, minimize latency, and deploy AI solutions efficiently using modern MLOps practices.

By the end of this training, participants will be able to:

  • Optimize DeepSeek models for efficiency, accuracy, and scalability.
  • Implement best practices for MLOps and model versioning.
  • Deploy DeepSeek models on cloud and on-premise infrastructure.
  • Monitor, maintain, and scale AI solutions effectively.
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Kubeflow

 35 Hours

This instructor-led, live training in Kansas (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 on AWS

 28 Hours

This instructor-led, live training in Kansas (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 Kansas (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.
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Kubeflow Fundamentals

 28 Hours

This instructor-led, live training in Kansas (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...

MLflow

 21 Hours

This instructor-led, live training in (online or onsite) is aimed at data scientists who wish to go beyond building ML models and optimize the ML model creation, tracking, and deployment process.

By the end of this training, participants will be able to:

  • Install and configure MLflow and related ML libraries and frameworks.
  • Appreciate the importance of trackability, reproducability and deployability of an ML model
  • Deploy ML models to different public clouds, platforms, or on-premise servers.
  • Scale the ML deployment process to accommodate multiple users collaborating on a project.
  • Set up a central registry to experiment with, reproduce, and deploy ML models.
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MLOps: CI/CD for Machine Learning

 35 Hours

This instructor-led, live training in Kansas (online or onsite) is aimed at engineers who wish to evaluate the approaches and tools available today to make an intelligent decision on the path forward in adopting MLOps within their organization.

By the end of this training, participants will be able to:

  • Install and configure various MLOps frameworks and tools.
  • Assemble the right kind of team with the right skills for constructing and supporting an MLOps system.
  • Prepare, validate and version data for use by ML models.
  • Understand the components of an ML Pipeline and the tools needed to build one.
  • Experiment with different machine learning frameworks and servers for deploying to production.
  • Operationalize the entire Machine Learning process so that it's reproduceable and maintainable.
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MLOps for Azure Machine Learning

 14 Hours

This instructor-led, live training in (online or onsite) is aimed at machine learning engineers who wish to use Azure Machine Learning and Azure DevOps to facilitate MLOps practices.

By the end of this training, participants will be able to:

  • Build reproducible workflows and machine learning models.
  • Manage the machine learning lifecycle.
  • Track and report model version history, assets, and more.
  • Deploy production ready machine learning models anywhere.
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Testimonials (2)

the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose

Guillaume GAUTIER - OLEA MEDICAL

Course - MLflow

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

MLOps for Azure Machine Learning

2025-09-08 9:30 am
14 hours
Overland Park, KS - Commerce Plaza
$ 2703 (Online)
$ 2703 (Classroom)

DeepSeek: Advanced Model Optimization and Deployment

2025-09-22 9:30 am
14 hours
Wichita, KS - Regus - Grand Hotel at Union Station
$ 2703 (Online)
$ 2703 (Classroom)

MLOps: CI/CD for Machine Learning

2025-10-06 9:30 am
35 hours
Overland Park, KS - Commerce Plaza
$ 6757 (Online)
$ 6757 (Classroom)

MLflow

2025-10-20 9:30 am
21 hours
Wichita, KS - Regus - Grand Hotel at Union Station
$ 4054 (Online)
$ 4054 (Classroom)

MLflow

2025-11-03 9:30 am
21 hours
Overland Park, KS - Commerce Plaza
$ 4054 (Online)
$ 4054 (Classroom)

MLflow

2025-11-17 9:30 am
21 hours
Wichita, KS - Regus - Grand Hotel at Union Station
$ 4054 (Online)
$ 4054 (Classroom)

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