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دوراتنا
Unix Tools: Data, Software and Production Engineering
Grow from being a Unix novice to Unix wizard status! Process big data, analyze software code, run DevOps tasks and excel in your everyday job through the amazing power of the Unix shell and command-line tools.
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Course by
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Self Paced
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32
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الإنجليزية
Machine Learning Engineering for Production (MLOps)
Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Effectively deploying machine learning…
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Course by
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Self Paced
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الإنجليزية
Machine Learning Data Lifecycle in Production
**Starting May 8, enrollment for the Machine Learning Engineering for Production Specialization will be closed.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Deploying Machine Learning Models in Production
**Starting May 8, enrollment for the Machine Learning Engineering for Production Specialization will be closed. Please enroll in this specialization or to individual courses by then to gain access to this course material.** In the fourth course of Machine Learning Engineering for Production Specialization, you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case.
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Course by
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Self Paced
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33 ساعات
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الإنجليزية
Machine Learning Modeling Pipelines in Production
**Starting May 8, enrollment for the Machine Learning Engineering for Production Specialization will be closed.
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Course by
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Self Paced
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48 ساعات
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الإنجليزية
Introduction to Machine Learning in Production
In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the process for developing, deploying, and continuously improving a productionized ML application.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية