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MUHAMMAD FAJAR ANDIKHA

Member since 2022

Diamond League

15880 points
Build Custom Processors with Document AI [Deprecated] Earned Mar 7, 2025 EST
Build Batch Data Pipelines on Google Cloud Earned Mar 6, 2025 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Mar 1, 2025 EST
Google Cloud 中的資料工程簡介 Earned Jan 31, 2025 EST
在 Agent Platform 設計提示 Earned Jan 31, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned Sep 5, 2024 EDT
探索生成式 AI - Agent Platform Earned Aug 24, 2024 EDT
Build a Certification Study Guide: PDE Exam Prep Earned Aug 6, 2024 EDT

Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.

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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.

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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 Managed Service for Apache Spark 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。

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在本課程中,您會學到 Google Cloud 上的資料工程、資料工程師的角色與職責,以及這些內容如何對應至 Google Cloud 提供的服務。您也將瞭解處理資料工程難題的許多方法。

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完成 在 Agent Platform 設計提示 技能徽章入門課程,即可證明您具備下列技能: 在 Agent Platform 設計提示、分析圖片,以及運用多模態模型生成內容。瞭解如何建立有效的提示、引導生成式 AI 輸出內容, 以及將 Gemini 模型用於實際的行銷情境。

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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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「探索生成式 AI - Agent Platform」課程包含一系列實驗室, 介紹如何在 Google Cloud 使用生成式 AI。完成這些實驗室之後,您會瞭解如何 在 Agent Platform 使用 Gemini 模型、提示詞設計技巧與最佳做法,以及 AI 在構思想法和文字分類、擷取、摘要等方面的用途。您也會瞭解如何運用 Agent Platform 的自訂訓練功能調整基礎模型, 並部署至 Agent Platform 中的端點。

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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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