New York (NYC) - Midtown Manhattan - Park Ave.

E48-49th (Grand Central), 299 Park Avenue, New York City, United States, 10171

The venue is located in between the Waldorf Astoria and J.P. Morgan and Chase.

NY, Long Island - Bohemia

80 Orville Drive Suite 100, Bohemia, united states, 11716

The venue is located just across the road from the Puritan's Pride Vitamin Factory Outlet and the Leidel Corporation building, just up the road from FedEx.

PA, Pittsburgh - Penn Center East Monroeville

201 Penn Center Boulevard Suite 400, Pittsburgh, United states, 15235

The venue is located in the neighborhood of the Penn Center, on the opposite side of the street to the Rey Azteca and Yamato restaurants and in the same building as Pearce Orthodontics.

New York (NYC) - Midtown Manhattan - Madison Ave.

E38-39th, 260 Madison Ave., New York, United States, 10016

The venue is located just opposite of Madison Av & E 38 St bus stop and Zuma NYC, in the same building as Chase Bank.

NY, Brooklyn - One Pierrepont Plaza

300 Cadman Plaza West, New York, united states, 11201

One Pierrepont Plaza is accessible via 12 nearby subway and bus lines. The building is conveniently located near the Brooklyn Bridge, the Manhattan Bridge and the Brooklyn-Queens Expressway. Long Island Rail Road within walking distance and 5 minutes to downtown Manhattan.

NY, Long Island - New Hyde Park

1979 Marcus Ave Suite 210, Long Island, united states, 11042

The Center is located within three miles from The Long Island Expressway, Northern State Parkway and MTA bus. There is fast access to amenities close by and an easy commute to the city with only 15 minutes drive to LaGuardia and Kennedy Airports.

CT, Stamford - Downtown

One Stamford Plaza, Stamford, united states, 06901

The venue is located just opposite of the Stamford Mariott Hotel & Spa and in the vicinity of the Stamford Town Center, H&M and Barnes&Noble.

CT, Hartford - Downtown

CT, Hardford - Downtown, 100 Pearl Street 14th floor, Hartford, united states, 06103

The venue is located right at the heart of the city's business district in the Greater Hartford Welcome Center, just opposite of the Pearl St and Lewis St bus station. This impressive two-tower office building features a three-story granite and glass lobby its own gym and a secure underground parking.

CT, East Berlin - East Berlin

East Berlin, 1224 Mill St. Building B - Suite 224, East Berlin, united states, 06023

The venue is located just off of Mill St in the vicinity of Haven, Inc.

PA, Philadelphia - International Plaza Dr Suite

1 International Plaza Dr Suite 550, Philadelphia, united states, 19153

The Center lies in the heart of Philadelphia with excellent highway access to I-95. It is in a short distance to City Center train depot, SEPTA bus and offers shuttle service to nearby Philadelphia International Airport.

NY, Queens - Forest Hills Tower

Queens Blvd Suite 400, New York, united states, 11375

This venue is situated on the corner with Grand Central Parkway / Jackie Robinson Parkway giving you quick subway access. It is conveniently located in less than 30 minutes from Long Island and only 15 minutes away from JFK and LaGuardia Airports.

NY, Staten Island - 1120 South Avenue

1120 South Ave, Staten Island, united states, 10314

This location is located right off the Staten Island Expressway, 6 miles from Historic Richmond Town and 7 miles from the Staten Island Ferry to Lower Manhattan.

Subcategories (2)

Category for Kubeflow

Kubeflow
Category for MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours

This instructor-led, live training in New York (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 New York (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 New York (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 New York (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 New York (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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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 New York (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

Kubeflow

2025-08-04 9:30 am
35 hours
CT, East Berlin - East Berlin
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow

2025-08-18 9:30 am
35 hours
PA, Philadelphia - International Plaza Dr Suite
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow on AWS

2025-09-01 9:30 am
28 hours
NY, Queens - Forest Hills Tower
$ 6371 (Online)
$ 8371 (Classroom)

DeepSeek: Advanced Model Optimization and Deployment

2025-09-11 9:30 am
14 hours
NY, Staten Island - 1120 South Avenue
$ 2703 (Online)
$ 3703 (Classroom)

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