Serverless Data Processing with Dataflow: Foundations
Earned May 24, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned May 22, 2023 EDT
Build Streaming Data Pipelines on Google Cloud
Earned May 18, 2023 EDT
Build Batch Data Pipelines on Google Cloud
Earned Apr 28, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Mar 25, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Jan 24, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Jan 15, 2023 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Jan 10, 2023 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Earned Jan 9, 2023 EST
建構安全的 Google Cloud 網路
Earned Jan 7, 2023 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud - Locales
Earned Jan 6, 2023 EST
在 Google Cloud 設定應用程式開發環境
Earned Jan 4, 2023 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned Jan 4, 2023 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Jan 1, 2023 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Earned Dec 29, 2022 EST
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.
了解详情
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.
了解详情
In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
了解详情
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
了解详情
This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
了解详情
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.
了解详情
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.
了解详情
完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Dataproc 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
了解详情
This course, Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud. The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Googl…
了解详情
完成「建構安全的 Google Cloud 網路」課程，即可獲得技能徽章。本課程將說明多項網路相關 資源，協助您在 Google Cloud 建構、調度資源和保護應用程式。
了解详情
This course, Google Cloud Computing Foundations: Networking & Security in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Networking & Security in Google Cloud.
The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Dat…
了解详情
只要修完「在 Google Cloud 設定應用程式開發環境」課程，就能獲得技能徽章。 在本課程中，您將學會如何使用以下技術的基本功能，建構和連結以儲存空間為中心的雲端基礎架構：Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。
了解详情
This course, Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Infrastructure in Google Cloud. The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google C…
This course, Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Cloud Computing Fundamentals .The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
…
Serverless Data Processing with Dataflow: Foundations
Earned May 24, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned May 22, 2023 EDT
Build Streaming Data Pipelines on Google Cloud
Earned May 18, 2023 EDT
Build Batch Data Pipelines on Google Cloud
Earned Apr 28, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Mar 25, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Jan 24, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Jan 15, 2023 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Jan 10, 2023 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Earned Jan 9, 2023 EST
建構安全的 Google Cloud 網路
Earned Jan 7, 2023 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud - Locales
Earned Jan 6, 2023 EST
在 Google Cloud 設定應用程式開發環境
Earned Jan 4, 2023 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned Jan 4, 2023 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Jan 1, 2023 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Earned Dec 29, 2022 EST