Who should attend this Kubeflow Training Course?
The Kubeflow Training Course is designed for those who want to get better at streamlining their Machine Learning Workflows via Kubeflow, an open-source Machine Learning platform. This DevOps Certification Course can be beneficial to variety of professionals, including:
- Data Scientists
- Software Developers
- Data Analysts
- Data Engineers
- DevOps Engineers
- Cloud Engineers
- AI and ML Experts
Prerequisites of the Kubeflow Training Course
There are no formal prerequisites for this Kubeflow Training Course.
Kubeflow Training Course Overview
Kubeflow is an essential platform for orchestrating and deploying Machine Learning (ML) and data science workflows on Kubernetes. In the rapidly evolving field of DevOps, mastering Kubeflow is crucial. Kubeflow streamlines the deployment of ML models, making it pertinent for DevOps professionals looking to enhance their skills in ML operations. This course equips learners with the knowledge to excel in DevOps by integrating Machine Learning seamlessly.
Proficiency in Kubeflow is imperative for DevOps professionals aiming to excel in their careers. It empowers them to manage complex ML pipelines efficiently, ensuring the seamless integration of ML models into their applications. This DevOps Certification Training is tailored for DevOps Practitioners, Data Engineers, and anyone seeking DevOps Certifications, as it equips them with the skills needed to navigate the increasingly data-driven world of DevOps.
In this 2-day Kubeflow Training, delegates will gain a deep understanding of Kubeflow and the development of Machine Learning pipelines. During this DevOps Certification, delegates will learn about the architecture and installation process of Kubeflow. They will also learn about the central dashboard that provides quick access to Kubeflow components deployed in a cluster. Our highly professional instructors with years of experience in teaching technical courses will conduct this training course.
Course Objectives
- To deploy Machine Learning systems to several environments for development
- To evaluate the output of many stages of the Machine Learning workflow
- To use Jupyter and TensorFlow in Kubeflow Notebooks effectively
- To set up Kubeflow with authentication and authorisation support through OIDC in Azure
- To identify the problems and collect data to train the Machine Learning model
- To evaluate the output of various stages and apply changes to the model
After completing this DevOps Certification Course, delegates will be equipped with the knowledge and skills needed to excel in DevOps roles requiring ML integration. This course serves as a solid foundation for those pursuing DevOps Certification, helping them stand out in the competitive field of DevOps.