Lausanne

Rue du Port-Franc 22, Lausanne, Switzerland, 1003

Overview

Our training facilities are located at Rue du Port-Franc 22 in Lausanne. Located on the fourth floor of a well-kept office building, our premises offer enough space for successful training courses in the heart of Lausanne.

 

Directions

The NobleProg training facilities are located in the heart of downtown Lausanne, the centre of this vibrant city.

 

Parking

Cars can be parked in the area along Rue du Port-Franc and the nearby side streets, even if you may have to search for a moment. There is no charge for parking.

 

Local Amenities

Around the Rue du Port-Franc there are numerous small restaurants and shops where you can eat well and cheaply. There are also some hotels close by if you need accommodation for the training.

Subcategories (2)

Image for the Kubeflow

Kubeflow
Image for the MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours
This instructor-led, live training in Lausanne (online or onsite) is aimed at advanced-level AI engineers and data scientists with intermediate-to-advanced experience who wish to enhance DeepSeek model performance, minimize latency, and deploy AI solutions efficiently using modern MLOps practices. By the end of this training, participants will be able to:
  • Optimize DeepSeek models for efficiency, accuracy, and scalability.
  • Implement best practices for MLOps and model versioning.
  • Deploy DeepSeek models on cloud and on-premise infrastructure.
  • Monitor, maintain, and scale AI solutions effectively.
Read more...

Kubeflow

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

MLflow

 21 Hours
This instructor-led, live training in (online or onsite) is aimed at data scientists who wish to go beyond building ML models and optimize the ML model creation, tracking, and deployment process. By the end of this training, participants will be able to:
  • Install and configure MLflow and related ML libraries and frameworks.
  • Appreciate the importance of trackability, reproducability and deployability of an ML model
  • Deploy ML models to different public clouds, platforms, or on-premise servers.
  • Scale the ML deployment process to accommodate multiple users collaborating on a project.
  • Set up a central registry to experiment with, reproduce, and deploy ML models.
Read more...

MLOps: CI/CD for Machine Learning

 35 Hours
This instructor-led, live training in Lausanne (online or onsite) is aimed at engineers who wish to evaluate the approaches and tools available today to make an intelligent decision on the path forward in adopting MLOps within their organization. By the end of this training, participants will be able to:
  • Install and configure various MLOps frameworks and tools.
  • Assemble the right kind of team with the right skills for constructing and supporting an MLOps system.
  • Prepare, validate and version data for use by ML models.
  • Understand the components of an ML Pipeline and the tools needed to build one.
  • Experiment with different machine learning frameworks and servers for deploying to production.
  • Operationalize the entire Machine Learning process so that it's reproduceable and maintainable.
Read more...

MLOps for Azure Machine Learning

 14 Hours
This instructor-led, live training in (online or onsite) is aimed at machine learning engineers who wish to use Azure Machine Learning and Azure DevOps to facilitate MLOps practices. By the end of this training, participants will be able to:
  • Build reproducible workflows and machine learning models.
  • Manage the machine learning lifecycle.
  • Track and report model version history, assets, and more.
  • Deploy production ready machine learning models anywhere.
Read more...

Last Updated:

Testimonials (2)

the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose

Guillaume GAUTIER - OLEA MEDICAL

Course - MLflow

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

MLOps: CI/CD for Machine Learning

2025-05-19 09:30
35 hours
Lausanne
8680 CHF (Online)
9930 CHF (Classroom)

Kubeflow on AWS

2025-06-02 09:30
28 hours
Lausanne
6944 CHF (Online)
7944 CHF (Classroom)

Kubeflow on AWS

2025-06-16 09:30
28 hours
Lausanne
6944 CHF (Online)
7944 CHF (Classroom)

MLflow

2025-06-30 09:30
21 hours
Lausanne
5208 CHF (Online)
5958 CHF (Classroom)

Kubeflow

2025-07-14 09:30
35 hours
Lausanne
9880 CHF (Online)
11130 CHF (Classroom)

Other regions in Switzerland

Other Countries

These courses are also available in other countries

Consulting

MLOps Consulting
Online MLOps training in Lausanne, MLOps training courses in Lausanne, Weekend MLOps courses in Lausanne, Evening MLOps training in Lausanne, MLOps instructor-led in Lausanne, MLOps on-site in Lausanne, Weekend MLOps training in Lausanne, MLOps trainer in Lausanne, MLOps instructor in Lausanne, MLOps private courses in Lausanne, MLOps instructor-led in Lausanne, MLOps one on one training in Lausanne, MLOps coaching in Lausanne, MLOps boot camp in Lausanne, MLOps classes in Lausanne, Evening MLOps courses in Lausanne, Online MLOps training in Lausanne