Digital 01 Building

No. 12, Guanghua Road, Chaoyang District, Beijing, China, 100000

Between the China International Trade Center and the Kerry Centre, it is backed by the International Trade Center and is across the street from Kerry Apartments, with a total construction area of 32,000 square meters. Peripheral package Shopping mall: Beijing Guomao Mall flagship store, Wanda New World Mall, Guiyou Shopping Mall Bank: Guangfa Bank International Trade Branch, Huaxia Bank Jingguang Sub-branch, Industrial Bank Guanghua Road Sub-branch, Huaxia Bank Guanghua Sub-branch, CITIC Bank Wealth Center Branch Hotel: Liandu Business Hotel, Home Inn, Jianguo Hotel, Wanda Sofitel Hotel, Jinglun Hotel, Beijing Bohao Ruiting Hotel, Beijing Kerry Hotel, Millennium Hotel Catering: Grandma's Kitchen, Xiaowangfu, Ganges Indian Restaurant, Shijiao Guoguomen Restaurant, etc.

Explore Our Courses

Kubeflow

 35 Hours
This instructor-led, live training in Beijing Chaoyang (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 Beijing Chaoyang (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 Beijing Chaoyang (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 Beijing Chaoyang (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...

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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 Fundamentals

2025-05-06 09:30
28 hours
Digital 01 Building

Kubeflow

2025-05-26 09:30
35 hours
Digital 01 Building

Kubeflow on Azure

2025-06-03 09:30
28 hours
Digital 01 Building

Kubeflow on Azure

2025-06-17 09:30
28 hours
Digital 01 Building

Kubeflow on AWS

2025-07-01 09:30
28 hours
Digital 01 Building

Kubeflow on AWS

2025-07-15 09:30
28 hours
Digital 01 Building

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Kubeflow Consulting
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