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Aditya Singh

Member since 2022

Bronze League

800 points
Smart Analytics, Machine Learning, and AI on Google Cloud Earned ديسمبر 13, 2022 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned نوفمبر 17, 2022 EST
Implementing Cloud Load Balancing for Compute Engine Earned نوفمبر 14, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals Earned نوفمبر 3, 2022 EDT

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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