AL, Birmingham - Perimeter Park

One Perimeter Park South Suite 100 N, Birmingham, united states, 35243

The Perimeter Park office space in Birmingham, Alabama has a new look since being remodeled with modern, relaxing decor. In the convenient first floor office space, Perimeter Park Center prides itself on award-winning customer service. Located on Highway 280 off Interstate I-459, the center is only 13 miles away from Birmingham International Airport. Surrounded with hotels, restaurants, upscale shops, as well as an excellent gym, the center is sure to provide for all our customers needs.

GA, Atlanta - Colony Square

1201 Peachtree St. NE,, Atlanta, united states, 30361

The venue is located in the heart of midtown Atlanta, on the second floor of the 400 building on the corner of 14th Street and Peachtree Street, which is connected to a well-known mall. The office building, which is in the cultural arts district of the city, was one of the first mixed-use developments in the south when it was constructed in the 1970s.

AL, Birmingham, Chase Corporate Dr Suite 400

Chase Corporate Dr Suite 400, Birmingham, united states, 35244

The venue is located just off of Montgomery Highway just down the road from the Courtyard by Marriott Birmingham Hoover.

GA, Atlanta - Proscenium

1170 Peachtree Street, Atlanta, United States, 30309

The venue is located across the street from Colony Square in the same building as Yahoo Inc.

GA, Decatur - One West Court Square

1 W Ct Square #750, Decatur, United States, 30030

The venue is located on One West Court Square right next door to the DeKalb History Center Museum.

Atlanta, GA - One Hartsfield

100 Hartsfield Centre Parkway, Atlanta, United States, 30354

The venue is located just up the road from the Concourse Atlanta Airport and next door to the Renaissance Concourse Atlanta Airport Hotel.

GA, Atlanta - Downtown 260 Peachtree

260 Peachtree St NW, Atlanta, united states, 30303

The Regus 260 Peachtree office space in Atlanta is located at 260 Peachtree Street in the prestigious HUB zone.

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 Georgia (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 Georgia (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 Georgia (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 Georgia (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 Georgia (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 Georgia (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.
Read more...

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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
AL, Birmingham - Perimeter Park
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow

2025-08-18 9:30 am
35 hours
AL, Birmingham, Chase Corporate Dr Suite 400
$ 6757 (Online)
$ 9257 (Classroom)

Kubeflow on AWS

2025-09-01 9:30 am
28 hours
AL, Birmingham - Perimeter Park
$ 6371 (Online)
$ 8371 (Classroom)

DeepSeek: Advanced Model Optimization and Deployment

2025-09-11 9:30 am
14 hours
AL, Birmingham, Chase Corporate Dr Suite 400
$ 2703 (Online)
$ 3703 (Classroom)

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