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This course provides a thorough introduction to MLOps, emphasizing the efficient deployment and management of ML models in production. It covers stages like development, deployment, monitoring, and optimization, with hands-on training in top MLOps tools to build scalable, production-ready workflows.
This course is well-suited for programmers, developers, data analysts, statisticians, data scientists, and software engineers.
To excel in MLOps, you need Python skills, ML algorithm knowledge, experience with Docker, Kubernetes, and cloud platforms. A laptop with at least 8GB RAM, Intel i3+ processor, and stable internet is also required.
Practicals for this course will be implemented using various tools and detailed step-by-step installation guidesfor these tools are available on the LMS. In case you come across any doubt, the 24*7 support teams will promptly assist you.
A professional training course that teaches end-to-end MLOps such as development, deployment, monitoring, and operations, using key tools and techniques in line with industry standards.
Yes, It includes live classes, hands-on labs, quizzes, and end-to-end real-world projects.
This training course covers AWS SageMaker, Azure ML, Google Cloud Platform, MLflow, Docker, Kubernetes, Jenkins, and more with AI tools.
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