Course Outline

Introduction

Overview of Kubeflow Features and Components

  • Containers, manifests, etc.

Overview of a Machine Learning Pipeline

  • Training, testing, tuning, deploying, etc.

Deploying Kubeflow to a Kubernetes Cluster

  • Preparing the execution environment (training cluster, production cluster, etc.)
  • Downloading, installing and customizing.

Running a Machine Learning Pipeline on Kubernetes

  • Building a TensorFlow pipeline.
  • Building a PyTorch pipleline.

Visualizing the Results

  • Exporting and visualizing pipeline metrics

Customizing the Execution Environment

  • Customizing the stack for diverse infrastructures
  • Upgrading a Kubeflow deployment

Running Kubeflow on Public Clouds

  • AWS, Microsoft Azure, Google Cloud Platform

Managing Production Workflows

  • Running with GitOps methodology
  • Scheduling jobs
  • Spawning Jupyter notebooks

Troubleshooting

Summary and Conclusion

Requirements

  • Familiarity with Python syntax 
  • Experience with Tensorflow, PyTorch, or other machine learning framework
  • A public cloud provider account (optional) 

Audience

  • Developers
  • Data scientists
 28 Hours

Delivery Options

Private Group Training

Our identity is rooted in delivering exactly what our clients need.

  • Pre-course call with your trainer
  • Customisation of the learning experience to achieve your goals -
    • Bespoke outlines
    • Practical hands-on exercises containing data / scenarios recognisable to the learners
  • Training scheduled on a date of your choice
  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

Private Group Prices RRP from €9120 online delivery, based on a group of 2 delegates, €2880 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.

Contact us for an exact quote and to hear our latest promotions


Public Training

Please see our public courses

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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 Fundamentals

2025-07-14 09:30
28 hours
Utrecht

Kubeflow Fundamentals

2025-07-28 09:30
28 hours
The Hague

Kubeflow Fundamentals

2025-08-11 09:30
28 hours
Nijmegen

Kubeflow Fundamentals

2025-08-25 09:30
28 hours
Wageningen

Kubeflow Fundamentals

2025-09-08 09:30
28 hours
Arnhem

Kubeflow Fundamentals

2025-09-22 09:30
28 hours
Leeuwarden

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