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This course is designed for engineers aiming to escalate Machine Learning workloads on Azure. Conducted by seasoned professionals, the training will take you through the intricacies of Kubeflow, Kubernetes, and TensorFlow.
What You Will Achieve:
• Grasp the nuances of Kubeflow and how it interfaces with Kubernetes.
• Acquire the skills to set up and manage Azure Kubernetes Service (AKS).
• Learn to create robust Kubernetes pipelines for ML model automation.
• Gain experience in multi-GPU and parallel machine training with TensorFlow.
• Extend ML capabilities with Azure's managed services.
• Familiarity with machine learning and cloud computing concepts.
• Basic understanding of containers (Docker) and orchestration (Kubernetes).
• Working knowledge of command-line interfaces.
• Python programming experience is beneficial but not mandatory.
*We know each team has their own needs and specifications. That is why we can modify the training outline per need.
1. Introduction:
2. Setting the Stage:
3. Building the Environment:
4. Deployment Infrastructure:
5. Data Management:
6. Training and Monitoring:
7. Post-Deployment:
8. Summary and Conclusion:
Hands-on learning with expert instructors at your location for organizations.
Master new skills guided by experienced instructors from anywhere.
