Davao, Topaz Tower Centre

4F Topaz Tower, Damosa IT , Lanang, Davao City, Philippines

The Centre in Topaz Tower is in a 5-storey building that houses BPOs and corporate offices in Damosa IT Park. Distance from Francisco Bangoy International Airport is 5 kms and estimated travel time from the airport to the building by car is 15 minutes. The tower is located within DAMOSA District, an urban mixed-use development that comprises the ANFLOCOR Corporate Center, Damosa Gateway, Damosa Market Basket, Damosa Business Center, and the PEZA-accredited Damosa IT Park – a synergistic hub where business meets leisure. Building strategically located near malls-SM Lanang & Abreeza Ayala Mall-and government & private institutions are within its proximity. Hotels such as Microtel by Wyndham-Davao and Park In by Radisson Davao and a good mix of restaurants are easily accessible from the centre. Other establishments near the centre are SGV Davao Office, Concentrix Davao, Ford Davao, Toyota Davao, Philippine Nikkei Jin Kai International School, and Mindanao Kokusai Daigaku School

Explore Our Courses

Kubeflow

 35 Hours
This instructor-led, live training in Davao City (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 Davao City (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 Davao City (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 Davao City (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 on AWS

2025-05-06 09:30
28 hours
Davao, Topaz Tower Centre
210712 PHP (Online)
227312 PHP (Classroom)

Kubeflow

2025-05-26 09:30
35 hours
Davao, Topaz Tower Centre
997530 PHP (Online)
1018280 PHP (Classroom)

Kubeflow Fundamentals

2025-06-03 09:30
28 hours
Davao, Topaz Tower Centre
210712 PHP (Online)
227312 PHP (Classroom)

Kubeflow on Azure

2025-06-17 09:30
28 hours
Davao, Topaz Tower Centre
210712 PHP (Online)
227312 PHP (Classroom)

Kubeflow

2025-07-07 09:30
35 hours
Davao, Topaz Tower Centre
997530 PHP (Online)
1018280 PHP (Classroom)

Kubeflow

2025-07-21 09:30
35 hours
Davao, Topaz Tower Centre
997530 PHP (Online)
1018280 PHP (Classroom)

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