The Hsinchu Wishun centre

HSR Hsinchu Station District Lots, 6/F, No.46 and No.47 in ShiHsin Section, Hsinchu, taiwan, 30274

The Hsinchu Wishun centre is located in the commercial area of Hsinchu THSR district. It only takes 1 minute walk to Hsinchu HSR station which is connected to the centre building and Train Neiwan line. With its convenient transport connectivity, it is also easy to access through National Highway No.1 and Expressway to Hsinchu Science Park (8km) and Hsinchu CBD (15km ). The centre is located at one of the very few grade A buildings in Hsinchu. The newly constructed building is with abundant local amenities, including restaurants, retail shops, recreation facilities and a hotel. Nearby parks and hotels include Shuizhen Forest Park and Hsinchu Sheraton hotel. Surrounded by hi-tech companies and high end residential communities, the location is a new hub for companies that are looking to grow and start their business in Hsinchu. Regus Hsinchu Wishun centre offers flexible workplace solutions to accommodate needs of all types and sizes with comprehensive services at a reasonable price.

Explore Our Courses

Kubeflow

 35 Hours
This instructor-led, live training in Hsinchu (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 Hsinchu (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 Hsinchu (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 Hsinchu (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

2025-05-12 09:30
35 hours
The Hsinchu Wishun centre
58500 NT$ (Online)
58500 NT$ (Classroom)

Kubeflow

2025-05-26 09:30
35 hours
The Hsinchu Wishun centre
58500 NT$ (Online)
58500 NT$ (Classroom)

Kubeflow

2025-06-09 09:30
35 hours
The Hsinchu Wishun centre
58500 NT$ (Online)
58500 NT$ (Classroom)

Kubeflow on AWS

2025-06-17 09:30
28 hours
The Hsinchu Wishun centre
39600 NT$ (Online)
39600 NT$ (Classroom)

Kubeflow on Azure

2025-07-01 09:30
28 hours
The Hsinchu Wishun centre
39600 NT$ (Online)
39600 NT$ (Classroom)

Kubeflow Fundamentals

2025-07-15 09:30
28 hours
The Hsinchu Wishun centre
39600 NT$ (Online)
39600 NT$ (Classroom)

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