Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Building Realtime Pipelines in Cloud Data Fusion
This is a self-paced lab that takes place in the Google Cloud console. In addition to batch pipelines, Data Fusion also allows you to create real-time pipelines, that can process events as they are generated. Currently, realtime pipelines execute using Apache Spark Streaming on Cloud Dataproc clusters. In this lab, you will learn how to build a streaming pipeline using Data Fusion.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
AI Workflow: Enterprise Model Deployment
This is the fifth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This course introduces you to an area that few data scientists are able to experience: Deploying models for use in large enterprises. Apache Spark is a very commonly used framework for running machine learning models. Best practices for using Spark will be covered in this course. Best practices for
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud
Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية