Online or onsite, instructor-led live Kubeflow training courses demonstrate through interactive hands-on practice how to use Kubeflow to build, deploy, and manage machine learning workflows on Kubernetes.
Kubeflow training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Kubeflow trainings in Saskatchewan can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Regina - Royal Bank Building
2002 11th Ave, Regina, Canada, S4P 0J3
Grow your business in one of Regina’s most prominent finance hubs. Build your base in the prestigious Royal Bank Building, home to several leading financial and professional services companies.
Impress your clients and colleagues with the building’s commanding city views before getting to work in stylish surroundings with plenty of natural light. You can also travel easily for work or pleasure, with the nearby Regina International Airport offering regular flights across Canada and beyond.
You'll be within a 10-minute drive of the University of Saskatchewan and Peter Zakreski Regional Park. This spa hotel is 0.1 mi (0.1 km) from Cielo and 0.4 mi (0.6 km) from Evelyn Edwards Park.
Prime Location in Regina's Financial District
Expand your business in the heart of one of Regina’s most prominent financial hubs. Establish your office in the prestigious Royal Bank Building, a landmark hosting top financial and professional services firms.
Impress clients and colleagues with stunning views of the city, then get to work in modern, light-filled surroundings designed for productivity. For business or leisure, enjoy easy access to the Regina International Airport, which offers frequent flights across Canada and beyond.
This instructor-led, live training in Saskatchewan (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.
This instructor-led, live training in Saskatchewan (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.
This instructor-led, live training in Saskatchewan (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.
This instructor-led, live training in Saskatchewan (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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Testimonials (2)
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
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