Namur, Hotel de Ville

NobleProg Namur, Rue de Fer, 48 , Namur, Belgium, 5000

Namur is a French-speaking city in Belgium, capital of Wallonia since 1986, and capital of the province of Namur. Occupied since the Neolithic period, the confluence of the Sambre and the Meuse saw the birth of the Roman city at the beginning of our era. Former stronghold of the Counts of Namur, attached to the house of Luxembourg and then to the Habsburg Empire, the citadel of Namur was the focus of many sieges over the years. Despite the damage suffered by the conflicts, the city retains a rich movable and immovable heritage. Today the regional capital, the city is the seat of the Parliament of Wallonia, the Walloon Government and the Public Service of Wallonia, but also the host city of the International Francophone Film Festival, the fairground arts festival Namur in May, the Festival Verdur Rock.

  • The nearest airport to the training center

    • Namur-Suarlee International Airport

  • Closest train station to the training center

    • Namur station

  • The closest car park to the training center

    • Central Parking Lot

  • Cafés restaurants bars nearby

    1. YAYAMI Restaurant
    2. Restaurant San Marino
    3. Bar Caprice d'Ambiance

    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 Namur (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 Namur (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 Namur (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 Namur (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 Namur (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.
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    MLOps: CI/CD for Machine Learning

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

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    Testimonials (3)

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

    Guillaume GAUTIER - OLEA MEDICAL

    Course - MLflow

    The quality of the explanations, and the large number of topics covered

    Hugo SECHIER - Expleo France

    Course - Kubeflow on AWS

    Machine Translated

    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

    2025-05-19 09:30
    35 hours
    Namur, Hotel de Ville
    6150 EUR (Online)
    7150 EUR (Classroom)

    Kubeflow

    2025-06-02 09:30
    35 hours
    Namur, Hotel de Ville
    6150 EUR (Online)
    7150 EUR (Classroom)

    MLflow

    2025-06-10 09:30
    21 hours
    Namur, Hotel de Ville
    3750 EUR (Online)
    4350 EUR (Classroom)

    DeepSeek: Advanced Model Optimization and Deployment

    2025-06-24 09:30
    14 hours
    Namur, Hotel de Ville
    2550 EUR (Online)
    2950 EUR (Classroom)

    MLOps: CI/CD for Machine Learning

    2025-07-14 09:30
    35 hours
    Namur, Hotel de Ville
    6150 EUR (Online)
    7150 EUR (Classroom)

    MLflow

    2025-07-22 09:30
    21 hours
    Namur, Hotel de Ville
    3750 EUR (Online)
    4350 EUR (Classroom)

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