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CB Center

Yuri Gagarin Blvd 10, MD-200, Chisinau, Moldova

CB Center, located at 10 Yuri Gagarin Boulevard in Chisinau, Moldova, occupies a strategic position on MD-200, a key road in the capital. Its location on this major thoroughfare enhances its accessibility for businesses and visitors. Being near the city center, it is well-placed to serve the professional community in Moldova, providing a modern base for work and meetings.

Explore Our Courses

Kubeflow Essentials: Build, Train & Serve with Kubernetes

 14 Hours

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

  • Navigate the Kubeflow ecosystem and core components.
  • Build reproducible workflows with Kubeflow Pipelines.
  • Run scalable training jobs on Kubernetes.
  • Serve machine learning models efficiently using Kubeflow Serving.

Format of the Course

  • Guided presentations and collaborative discussions.
  • Hands-on labs with real Kubeflow components.
  • Practical exercises to build end-to-end ML workflows.

Course Customization Options

  • Customized versions of this training can be arranged to align with your team’s technology stack and project requirements.
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Kubeflow

 35 Hours

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

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Testimonials (1)

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 Essentials: Build, Train & Serve with Kubernetes

2026-06-24 09:30
14 hours
CB Center
540 EUR (Online)
540 EUR (Classroom)

Kubeflow

2026-07-08 09:30
35 hours
CB Center
1620 EUR (Online)
1620 EUR (Classroom)

Kubeflow

2026-07-22 09:30
35 hours
CB Center
1620 EUR (Online)
1620 EUR (Classroom)

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These courses are also available in other countries

Consulting

Kubeflow Consulting
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