Machine Learning Operations (MLOps): Getting Started
With an emphasis on CI/CD, cloud architecture, and training workflows, this course covers MLOps technologies and best practices for installing, assessing, and running ML systems on Google Cloud.
Description for Machine Learning Operations (MLOps): Getting Started
Features of the Course:
Fundamental Technologies for MLOps: Recognize and utilize the fundamental technologies necessary for facilitating effective MLOps, hence ensuring the efficient deployment and administration of machine learning models in a production environment.
Best Practices for Continuous Integration and Continuous Deployment: Implement optimal CI/CD methods for machine learning systems to guarantee continuous integration and deployment of models.
Google Cloud Architecture for MLOps: Acquire the skills to configure and provision Google Cloud architectures that provide dependable and efficient MLOps environments for scaled machine learning operations.
Training and Inference Procedures: Establish dependable and consistent training and inference workflows that guarantee the resilience and scalability of machine learning models in production.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 2 hours (approximately)
Schedule: Flexible
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