Course in Machine Learning Operations (MLOPS)
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Syllabus
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Summary
This course in Machine Learning Operations (MLOPS) provides a complete vision of automatic learning project management, highlighting the automation, implementation and monitoring of models in production environments. During the entire training, the acquisition of data, configuration of development environments and advanced tools such as MLFlow, Kubeflow and Prometheus is addressed. Through comparisons with Devops and Dataops, students are prepared to integrate MLOPS in various industries, optimizing the performance and reliability of ML models. In addition, it covers the prevention of models and guarantees compliance with quality standards thanks to the use of all these technologies.
Goals
Professional opportunities
To prepare you
The course in Machine Learning Operations (MLOPS) prepares you to efficiently manage automatic learning projects in all its phases, from data acquisition to the monitoring and maintenance of production models. You will learn to implement automation, testing and monitoring tools, integrating mlops with existing systems to guarantee the scalability and reliability of ML models.
Who is it addressed to?
This course in Machine Learning Operations (MLOPS) is aimed at data professionals, software engineering, data science and automatic learning specialists who seek to optimize the implementation and management of ML models in production, as well as automate development processes and improve the quality of their systems through the integration of MLOPS.
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