Montreal - Rene Levesque

1250 Rene Levesque Boulevard West, Montreal, Canada, H3B 4W8

Located in downtown Montréal, the building has metro stations and highways nearby, giving you quick and easy transport across the city and beyond.

Saint Laurent- Dr. Frederik-Philips

1111 Dr. Frederik-Philips Boulevard, Saint Laurent, Canada, H4M 2X6

Conveniently located close to highway 40 and the Cote-Vertu metro station with many restaurants nearby.

Laval - Daniel Johnson Boulevard

2572 Daniel-Johnson Boulevard, Laval, Canada, H7T 2R3

Located in Laval's central business district our 2572 Daniel Johnson Boulevard workspace is in the heart of a hi-tech neighbourhood, close to Biotech City and easily accessible from downtown Montreal or via highways A-15 and A-460.

Pointe Claire - Transcanada

6500 TransCanada Service Road, Pointe Claire, Canada, H9R 0A5

Designed by an industry-leading architect and equipped with the latest energy-efficient technology. Host overseas clients and travel for business easily from this sought-after location, with Montréal-Trudeau airport a 10-minute drive away.

Brossard - Complexe Dix 30

1040 Lux Street # 410, Brossard, Canada, J4Y 0E3

Commercial lifestyle centre Quartier DIX30. Well-located next to Autoroute des Cantons-de-l’est, downtown Montreal in less than 20 minutes away.

Levis - de Courchevel Street

1190B de Courchevel Street, Levis, Canada, G6W 0M6

De Courchevel Street is a home of flourishing community of technology, research and development with convenient transport links nearby for easy access across Québec and beyond.

Montreal - University Street

2001 Blvd. Robert Bourassa, Montreal, Canada, H3A 2A6

The University Street Center occupies an office building in the heart of the Montreal business district. It is nestled among the many skyscrapers of Downtown Montreal and has a direct connection to the world's largest underground complex.

Quebec - Sainte Foy

2828 Boulevard Laurier, Suite 700, Quebec City, Canada, G1V 0B9

Strategically placed near the international airport and the intersection of major roads, the center neighbors include the University Laval, shops, hotels, and many businesses.

Gatineau - Montcalm Street

200 Montcalm Street, Gatineau , Canada, J8Y 3B5

Located in Canada's National Capital Region on the main intersection in downtown Gatineau.

Québec-Lebourgneuf Business Centre

Suite 400, Rue de la Couronne, Québec, Canada, G1K 6P4

Prime Business Location in the Heart of Québec City Establish your business in one of Québec City’s vibrant commercial hubs. Our office space at the Lebourgneuf Business Centre, conveniently located just off Highway 40, is easily accessible by car—or leave your vehicle behind and make use of the on-site bike storage. Work efficiently in bright, fully-furnished offices designed for productivity, equipped with everything you need to succeed. When it’s time for a break, unwind in the comfortable lounge area. After a productive day, enjoy shopping or dining at the nearby Galeries de la Capitale mall.

Quebec City - Complexe Jules Dallaire

2828 Boulevard Laurier, Quebec City, Canada, G1V 0B9

Located in the prestigious Complexe Jules Dallaire development, easy to reach thanks to the area’s convenient transport links.

Subcategories (2)

Kubeflow

Kubeflow
MLflow

MLflow

Explore Our Courses

DeepSeek: Advanced Model Optimization and Deployment

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

Upcoming Courses

Kubeflow

2025-06-30 09:30
35 hours
Québec-Lebourgneuf Business Centre
CA$ 8,784 (Online)
CA$ 13,134 (Classroom)

MLOps: CI/CD for Machine Learning

2025-07-14 09:30
35 hours
Québec-Lebourgneuf Business Centre
CA$ 8,784 (Online)
CA$ 13,134 (Classroom)

MLflow

2025-07-22 09:30
21 hours
Québec-Lebourgneuf Business Centre
CA$ 5,270 (Online)
CA$ 7,880 (Classroom)

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These courses are also available in other countries

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