CA, Sacramento - Promenade Circle

180 Promenade Circle, Sacramento, United States, 95834

The venue is located just off the Dwight D. Eisenhower Highway, in the vicinity of The Promenade and Best Buy.

Regus - California Downtown Sunnyvale

640 W California Ave, Sunnyvale, United States, 94086

The Sunnyvale center is located one block from Caltrain rail station and provides easy access to Central Expressway and Highway 101. It is in walking distance to the city's downtown district, featuring numerous restaurants, shops, and businesses, as well as a short drive from San Jose International Airport.

CA, San Francisco - Golden Gate

75 Broadway, San Francisco , united states, 94111

With its fabulous arched windows, the 75 Broadway office, located in the heart of Jackson Square, is designed to impress. Situated at Golden Gateway Commons on the second floor of this unique campus-style building, it overlooks the green terrain's of Sydney Walton Park with the famous waterfront piers behind. This enviable location is a short walk from public transport and just blocks away from the Embarcadero and the ferry building, as well as a host of convenient amenities.

CA, Los Angeles - US Bank Tower

633 West 5th Street, Los Angeles, united states, 90071

Located in the heart of Downtown Los Angeles, in a short drive from the Union Station and few minutes away from U.S 101 & U.S.110 Highways.

CA, San Jose - Downtown

177 Park Avenue, San Jose, united states, 95113

The venue is located in the heart of downtown San Jose with quick access to Highways 87, 280 or the CalTrain.

San Diego Little Italy

1420, Kettner Boulevard, San Diego, United States, 92101

Situated in a prime location on the fringe of Little Italy, easy access to the Broadway Pier Ferry Terminal and is just a short 10-minute journey from the Maritime Museum of San Diego.

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 California (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.
Read more...

Kubeflow

 35 Hours

This instructor-led, live training in California (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 California (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 California (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.
Read more...

Kubeflow on Azure

 28 Hours

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

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 California (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
CA, San Jose - Downtown
$ 6757 (Online)
$ 9007 (Classroom)

Kubeflow

2025-08-18 9:30 am
35 hours
CA, San Jose - Downtown
$ 6757 (Online)
$ 9007 (Classroom)

Kubeflow on AWS

2025-09-01 9:30 am
28 hours
CA, San Jose - Downtown
$ 6371 (Online)
$ 8171 (Classroom)

DeepSeek: Advanced Model Optimization and Deployment

2025-09-11 9:30 am
14 hours
CA, San Jose - Downtown
$ 2703 (Online)
$ 3603 (Classroom)

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