Porto

NobleProg Porto, Av. da Boavista 1466, Porto, portugal, 4100-114

Our Venue is located on the city center of Porto, well connect by public transportation, with easy access by car with many options of parking places around the area. Surrounded by a large number of restaurants and commercial centres.

Four Points by Sheraton Matosinhos

188, Rua Sousa Aroso 188, 4450-286 Matosinhos, Matosinhos, Portugal, 4450-286 Matosinhos

Whether you travel for business, leisure or bleisure, Four Points by Sheraton Matosinhos welcomes you with four-star comfort, outstanding service and an ideal location in the city. The hotel offers a wide variety of facilities and services including a business center. Matosinhos beach is only 5 minutes walking distance from the hotel, perfect for surfing and other water sports. As a fishing area, local restaurants offer you the most wonderful fresh fishes and sea food for your delight.

Holiday Inn Porto - Gaia

220, Rua Diogo Macedo, 220, Vila Nova de Gaia 4400-107 , Gaia, Portugal

Hotel Central Parque

83, Av. Visc. de Barreiros 83, 4470-151 Maia, Maia, Portugal, 4470-151 Maia

Hotel Central Parque **** is located in the center of the city of Maia, due to its proximity to Francisco Sá Carneiro Airport, Zona Industrial da Maia, Exponor Matosinhos, the metro station and the main highways, it becomes the place ideal for your stay.

Explore Our Courses

Kubeflow

 35 Hours
This instructor-led, live training in Porto (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.
Read more...

Kubeflow Fundamentals

 28 Hours
This instructor-led, live training in Porto (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 Porto (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 Porto (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

Provisional Upcoming Courses (Contact Us For More Information)

Kubeflow on Azure

2025-05-19 09:30
28 hours
Porto

Kubeflow on AWS

2025-06-02 09:30
28 hours
Porto

Kubeflow on AWS

2025-06-16 09:30
28 hours
Porto

Kubeflow on Azure

2025-06-30 09:30
28 hours
Porto

Kubeflow Fundamentals

2025-07-14 09:30
28 hours
Porto

Kubeflow

2025-07-28 09:30
35 hours
Porto

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Kubeflow Consulting
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