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Kubeflow on AWS
28 HoursKubeflow on Azure
28 HoursKubeflow on GCP
28 HoursKubeflow on IBM Cloud
28 HoursMLOps: CI/CD for Machine Learning
35 HoursKubeflow
35 HoursKubeflow on OpenShift
28 HoursKubeflow Fundamentals
28 HoursMLflow
21 HoursLast Updated:
Testimonials (3)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
La qualité des explications, et le nombre important de sujets abordés
Hugo SECHIER - Expleo France
Course - Kubeflow on AWS
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.