加入 登录

Lawrence Godfrey

成为会员时间：2023

钻石联赛

33380 积分
Serverless Data Processing with Dataflow: Operations Earned Aug 31, 2024 EDT
使用 Knowledge Catalog 构建数据网格 Earned Mar 30, 2024 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Mar 23, 2024 EDT
使用 BigQuery 构建数据仓库 Earned Mar 17, 2024 EDT
Serverless Data Processing with Dataflow: Develop Pipelines Earned Mar 2, 2024 EST
Serverless Data Processing with Dataflow: Foundations Earned Feb 17, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Feb 11, 2024 EST
Build Streaming Data Pipelines on Google Cloud Earned Feb 4, 2024 EST
Build Batch Data Pipelines on Google Cloud Earned Jan 30, 2024 EST
Generative AI Fundamentals - 简体中文 Earned Jan 26, 2024 EST
负责任的 AI 简介 Earned Jan 25, 2024 EST
大型语言模型简介 Earned Jan 25, 2024 EST
生成式 AI 简介 Earned Jan 23, 2024 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned Jan 22, 2024 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Jan 16, 2024 EST
Build a Certification Study Guide: PDE Exam Prep Earned Jan 12, 2024 EST
在 Google Cloud 上为机器学习 API 准备数据 Earned Jan 7, 2024 EST
Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI Earned Jan 7, 2024 EST

In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.

了解详情

完成入门技能徽章课程使用 Knowledge Catalog 构建数据网格，展示以下方面的技能：使用 Knowledge Catalog 构建数据网格， 以在 Google Cloud 上实现数据安全、治理和发现。您将在 Knowledge Catalog 中练习和测试自己在标记资产、分配 IAM 角色和评估数据质量方面的技能。

了解详情

完成中级技能徽章课程利用 BigQuery ML 构建预测模型时的数据工程处理， 展示自己在以下方面的技能：利用 Dataprep by Trifacta 构建 BigQuery 数据转换流水线； 利用 Cloud Storage、Dataflow 和 BigQuery 构建提取、转换和加载 (ETL) 工作流； 以及利用 BigQuery ML 构建机器学习模型。

了解详情

完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。

了解详情

In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.

了解详情

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

完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程，赢取技能徽章。通过最终测验，即表明您理解了生成式 AI 的基本概念。 技能徽章是由 Google Cloud 颁发的数字徽章，旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中，以此来分享您获得的成就。

了解详情

这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。

了解详情

这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

了解详情

这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

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

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.

了解详情

完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据，展示以下技能： 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Managed Service for Apache Spark 中创建集群和运行 Apache Spark 作业，以及调用机器学习 API，包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

了解详情

Google Cloud 云计算基础课程面向没有或很少有云计算基础或经验的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。 完成本系列课程后，学员将能够清晰阐述这些概念，并掌握一些实际操作技能。 课程应按以下顺序完成： 1. Google Cloud 云计算基础课程：云计算基础知识 2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI 本课程是该系列课程的最后一门，回顾了托管式大数据服务、机器学习及其价值，以及如何通过获得技能徽章来进一步展示您在 Google Cloud 方面的技能。

了解详情