Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Jul 16, 2024 EDT
[CEPF L300 Course]: Data Analytics
Earned May 31, 2024 EDT
Launching into Machine Learning
Earned Apr 11, 2024 EDT
Google Cloud 上的 AI 和机器学习简介
Earned Jan 22, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Dec 18, 2023 EST
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Dec 16, 2023 EST
Build Streaming Data Pipelines on Google Cloud
Earned Dec 14, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Sep 30, 2023 EDT
探索生成式 AI - Agent Platform
Earned Aug 3, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Jul 12, 2023 EDT
Build Batch Data Pipelines on Google Cloud
Earned Jul 9, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Jul 4, 2023 EDT
在 Cloud Storage 上创建安全的数据湖
Earned Jun 27, 2023 EDT
使用 Dataplex 整理和治理数据
Earned Jun 24, 2023 EDT
负责任的 AI 简介
Earned Jun 12, 2023 EDT
编码器-解码器架构
Earned May 27, 2023 EDT
创建图片标注模型
Earned May 27, 2023 EDT
图像生成简介
Earned May 27, 2023 EDT
Transformer 模型和 BERT 模型
Earned May 27, 2023 EDT
注意力机制
Earned May 27, 2023 EDT
大型语言模型简介
Earned May 27, 2023 EDT
生成式 AI 简介
Earned May 27, 2023 EDT
Google Cloud 基础知识
Earned Dec 2, 2021 EST
Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
了解详情
Gemini Enterprise 结合了 Google 在搜索和 AI 领域的专长。它是一款强大的工具，让员工只需通过一个搜索栏，就能从文档库、邮件、聊天消息、工单系统及其他数据源中查找具体信息。Gemini Enterprise 助理还能帮助进行头脑风暴、开展研究、生成文档大纲并执行其他操作，比如邀请同事参加某个日历活动。因此它能加快知识型工作的进度并提升协作效率。（请注意，Gemini Enterprise 以前称为 Google Agentspace，本课程中可能会提及以前的产品名称。）
了解详情
This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
了解详情
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
了解详情
This Data Analytics course consists of a series of advanced-level labs designed to validate your proficiency in using Google Cloud services. Each lab presents a set of the required tasks that you must complete with minimal assistance. The labs in this course have replaced the previous L300 Data Analytics Challenge Lab. If you have already completed the Challenge Lab as part of your L300 accreditation requirement, it will be carried over and count towards your L300 status. You must score 80% or higher for each lab to complete this course, and fulfill your CEPF L300 Data Analytics requirement. For technical issues with a Challenge Lab, please raise a Buganizer ticket using this CEPF Buganizer template: go/cepfl300labsupport
了解详情
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
了解详情
本课程介绍 Google Cloud 的 AI 和机器学习 (ML) 能力，重点讲解如何开发生成式和预测式 AI 项目。本课程将探讨“数据到 AI”全生命周期中的多种技术、产品和工具，并通过互动练习帮助数据科学家、AI 开发者和机器学习工程师提升专业能力。
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
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
探索生成式 AI - Agent Platform”课程包含一系列实验， 指导用户在 Google Cloud 平台上使用生成式 AI。通过这些实验，您将了解 如何在 Agent Platform 中使用 Gemini 模型。您还将了解提示设计、最佳实践， 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本摘要等。此外， 您将学习如何通过 Agent Platform 中的自定义训练来训练基础模型， 从而对其进行调优，以及如何将其部署到 Agent Platform 中的端点。
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
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
完成在 Vertex AI 上构建和部署机器学习解决方案课程，赢取中级技能徽章。 在此课程中，您将了解如何使用 Google Cloud 的 Vertex AI Platform、AutoML 以及自定义训练服务来 训练、评估、调优、解释和部署机器学习模型。 此技能徽章课程的目标受众是专业的数据科学家和机器学习 工程师。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程 和作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。
Build a Certification Study Guide: PMLE
Earned Apr 29, 2025 EDT
借助 Gemini Enterprise 加速知识交流
Earned Apr 7, 2025 EDT
Feature Engineering
Earned Aug 6, 2024 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Jul 16, 2024 EDT
[CEPF L300 Course]: Data Analytics
Earned May 31, 2024 EDT
Launching into Machine Learning
Earned Apr 11, 2024 EDT
Google Cloud 上的 AI 和机器学习简介
Earned Jan 22, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Dec 18, 2023 EST
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Dec 16, 2023 EST
Build Streaming Data Pipelines on Google Cloud
Earned Dec 14, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Sep 30, 2023 EDT
探索生成式 AI - Agent Platform
Earned Aug 3, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Jul 12, 2023 EDT
Build Batch Data Pipelines on Google Cloud
Earned Jul 9, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案
Earned Jul 4, 2023 EDT
在 Cloud Storage 上创建安全的数据湖
Earned Jun 27, 2023 EDT
使用 Dataplex 整理和治理数据
Earned Jun 24, 2023 EDT
负责任的 AI 简介
Earned Jun 12, 2023 EDT
编码器-解码器架构
Earned May 27, 2023 EDT
创建图片标注模型
Earned May 27, 2023 EDT
图像生成简介
Earned May 27, 2023 EDT
Transformer 模型和 BERT 模型
Earned May 27, 2023 EDT
注意力机制
Earned May 27, 2023 EDT
大型语言模型简介
Earned May 27, 2023 EDT
生成式 AI 简介
Earned May 27, 2023 EDT
Google Cloud 基础知识
Earned Dec 2, 2021 EST