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Sasikumar Srinivasan
Date d'abonnement : 2021
Ligue d'Or
21015 points
Implementing Cloud Load Balancing for Compute Engine
Earned jan. 27, 2024 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned nov. 21, 2023 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned nov. 14, 2023 EST
Build a Certification Study Guide: PDE Exam Prep
Earned nov. 14, 2023 EST
Implement Event-Driven Messaging and Automation Workflows
Earned nov. 9, 2023 EST
Introduction to Generative AI
Earned nov. 9, 2023 EST
Build a Data Warehouse with BigQuery
Earned nov. 9, 2023 EST
Serverless Data Processing with Dataflow: Foundations
Earned nov. 7, 2023 EST
Understanding LookML in Looker
Earned oct. 10, 2021 EDT
Prepare Data for Looker Dashboards and Reports
Earned oct. 9, 2021 EDT
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.
En savoir plus
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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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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Earn a skill badge by completing the Implement Event-Driven Messaging and Automation Workflows skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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In this course, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
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