FL, Jacksonville - Deerwood Park

Deerwood Park, 10151 Deerwood Park Boulevard, Building 200, Suite 250, Jacksonville, United States, 32256

The venue is located in the neighborhood of the Chase Home Finance and the Florida Capital Bank, just behind the Cisco Systems building.

FL, Miami Airport - Waterford

6303 Blue Lagoon Drive Suite 400, Miami, united states, 33126

The venue is located right behind Miami Airport in front of Red-tailed Hawk Lake and in the same building as Johnson and Johnson.

FL, Tampa - Wells Fargo Center, 100 S. Ashley Drive Suite 600, Tampa, FL

100 S. Ashley Drive Suite 600, Tampa, United States, 33602

The venue is located in the Wells Fargo Center just next to the Tampa Convention Center parking.

FL, Orlando – GAI Building

618 E. South Street Suite 500, Orlando, United States, 32801

The venue is located in the GAI Building with the CNS Healthcare logo at the front.

FL, Jacksonville - Bank of America Tower

50 N. Laura Street Suite 2500, Jacksonville, United States, 32202

The office is located in a premier office tower in Downtown Jacksonville on the 42nd floor. This Class A LEED Certified building is situated in the Northbank Office Market Preeminent location that provides commanding views. Downtown Trolley and Bus stops are located just across the street on Forsyth with easy access to I-95 leading to I-10 and I-295. Convenient to Jacksonville International Airport, the building is also just minutes to Everbank Field, Jacksonville Landing, Times Union Performing Arts Center, Jacksonville Veterans Memorial Arena and Jacksonville Public Library. Spectacular views of the St John's River in Jacksonville, Florida are one of many features that make the Bank of America Tower office space stand out. The office space occupies a blue granite tower in the heart of the city's central business district. The iconic tower is one of the best-known business premises in the southeastern United States and includes a statement lobby and class-A workspace. Businesses of all kinds appreciate Jacksonville's location at the crossroads of three major railroads and three interstates, and its international airport.

FL, Tallahassee – Alliance Center

113 South Monroe Street 1st Floor, Tallahassee, united states, 32301

The venue is located in the Alliance Center across the street from FUBA and the Florida Optometric Association.

FL, West Palm Beach - Philips Point

777 South Flagler Drive, West Palm Beach, United States, 33401

The venue is located in the Philips Point building just off the Royal Park Bridge.

FL, Aventura - Corporate Center

20801 Biscayne Blvd., Miami, united states, 33180

The venue is located in the Grove Bank & Trust building just off Biscayne Blvd.

FL, Fort Lauderdale - Corporate Center

Corporate Center, 110 East Broward Blvd., Fort Lauderdale, United States, 33301

The venue is located in the Corporate Center across the street from the Uniform Advantage Corporate Office and just next door to Colliers International.

FL, Miami Beach - Miami Beach

1688 Meridian Ave #700, Miami Beach, United States, 33139

The venue is located at the crossing of Meridan Avenue and 17th St, just across the road the road from Macy's.

Subcategories (2)

Kubeflow

Kubeflow
MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours
This instructor-led, live training in Florida (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 Florida (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 Florida (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.
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Kubeflow on AWS

 28 Hours
This instructor-led, live training in Florida (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 Florida (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 Florida (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

2025-06-30 9:30 am
35 hours
FL, West Palm Beach - Philips Point
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow

2025-07-14 9:30 am
35 hours
FL, Aventura - Corporate Center
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow on AWS

2025-07-28 9:30 am
28 hours
FL, Fort Lauderdale - Corporate Center
$ 6371 (Online)
$ 8371 (Classroom)

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