Hasselt

Holiday Inn Hasselt, Kattegatstraat 1, Hasselt, Belgium, 3500 Hasselt

Holiday Inn Hasselt's 5 modern meeting rooms can accommodate up to 250 delegates. All meeting rooms have natural daylight. Free wireless internet throughout the hotel. Welcome coffee and coffee breaks will be served in our lobby by our friendly staff. City center hotel, next to the harbour! Modern Hasselt hotel offers free WiFi, a brasserie, and a mini gym Holiday Inn® Hasselt places you close to the city's central bars and restaurants. A 10-minute walk away, Hasselt station is served by local and regional trains. Hotel guests enjoy on-site parking discounts. Brussels Airport is a 50-minute drive away and Liège Airport is just 35 minutes away. Around the corner from the hotel, Modemuseum Hasselt traces the history of fashion with collections from the 18th century to the present. Five minutes away, the Jenevermuseum examines jenever, Belgium's juniper-flavoured national liquor. Stroll past cherry trees and koi ponds in the Japanese Garden, a 20-minute walk from the hotel. Opposite the park, the Trixxo Arena hosts international concert and event programmes. Here for work? Host up to 250 delegates in the hotel's five naturally lit meeting rooms. Catering is available upon request and there's free WiFi throughout the hotel. Enjoy city or canal views from the stylish guestrooms of this welcoming hotel where kids stay and eat free. Start your day with a buffet breakfast in the hotel's modern Brasserie De Boulevard, and enjoy our traditional Belgian cuisine. Unwind with a mini gym workout or a sauna session before meeting friends for drinks at the bar.

Subcategories (2)

Kubeflow

Kubeflow
MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

 14 Hours
This instructor-led, live training in Hasselt (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.
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Kubeflow

 35 Hours
This instructor-led, live training in Hasselt (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 Hasselt (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.
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Kubeflow on AWS

 28 Hours
This instructor-led, live training in Hasselt (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 Hasselt (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.
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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 Hasselt (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.
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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.
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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
Hasselt
6150 EUR (Online)
8650 EUR (Classroom)

Kubeflow

2025-06-02 09:30
35 hours
Hasselt
6150 EUR (Online)
8650 EUR (Classroom)

MLflow

2025-06-10 09:30
21 hours
Hasselt
3750 EUR (Online)
5250 EUR (Classroom)

DeepSeek: Advanced Model Optimization and Deployment

2025-06-24 09:30
14 hours
Hasselt
2550 EUR (Online)
3550 EUR (Classroom)

MLOps: CI/CD for Machine Learning

2025-07-14 09:30
35 hours
Hasselt
6150 EUR (Online)
8650 EUR (Classroom)

MLflow

2025-07-22 09:30
21 hours
Hasselt
3750 EUR (Online)
5250 EUR (Classroom)

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Consulting

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