Dmytro Kainara
成为会员时间:2021
白银联赛
21515 积分
成为会员时间:2021
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you will use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
Cloud Storage、Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服務, 可用於儲存、處理及管理資料。您可以整合運用這三種服務, 打造各式各樣的資料導向應用程式。在這個技能徽章課程中, 您將使用 Cloud Storage 儲存圖片、透過 Cloud Functions 處理, 並利用 Cloud Pub/Sub 將圖片傳送至其他應用程式。
This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.
完成「開始使用 Dataplex」技能徽章入門課程, 即可證明您具備下列技能:建立 Dataplex 資產、建立切面類型、 並將切面套用至 Dataplex 中的項目。
Earn a skill badge by completing the Get Started with Looker quest, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.
Earn a skill badge by completing the Share Data Using Google Data Cloud course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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。 「技能徽章」是 Google Cloud 核發的獨家數位徽章,用於表彰您相當熟悉 Google Cloud 產品與服務,並已通過測驗,能在互動式實作環境中應用相關知識。只要完成這個技能徽章課程和最終評量挑戰研究室,即可取得技能徽章並與親友分享成就。
完成 透過 BigQuery 建構資料倉儲 技能徽章中階課程,即可證明您具備下列技能: 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表, 以及在 BigQuery 使用 JSON、陣列和結構體。 「技能徽章」是 Google Cloud 核發的獨家數位徽章, 用於肯定您在 Google Cloud 產品和服務方面的精通程度, 代表您已通過測驗,能在互動式實作環境中應用相關 知識。完成技能徽章課程及結業評量挑戰研究室, 即可取得技能徽章並與他人分享。
本課程介紹 Google Cloud 中的 AI 和機器學習 (ML) 服務。這些服務可建構預測式和生成式 AI 專案。我們將帶您探索「從資料到 AI」生命週期中適用的技術、產品和工具,包括 AI 基礎、開發選項及解決方案。課程目的是藉由生動的學習體驗與實作練習,增進數據資料學家、AI 開發人員和機器學習工程師的技能與知識。
完成「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程,即可證明您具備下列技能: 可使用 BigQuery ML 建立及評估機器學習模型,並根據資料進行預測。 「技能徽章」是 Google Cloud 核發的獨家數位徽章, 用於肯定您在 Google Cloud 產品和服務方面的精熟技能, 代表您已通過測驗,能在互動式實作環境中應用相關知識。完成 本課程及結業評量挑戰實驗室,即可取得技能徽章 並與他人分享。
完成 從 BigQuery 資料取得深入分析結果 技能徽章入門課程,即可證明您具備下列技能: 撰寫 SQL 查詢、查詢公開資料表、將樣本資料載入 BigQuery、使用 BigQuery 的查詢驗證工具 排解常見語法錯誤,以及在 Looker Studio 中 透過連結 BigQuery 資料建立報表。 「技能徽章」是 Google Cloud 核發的獨家數位徽章, 用於肯定您在 Google Cloud 產品和服務方面的精通程度,代表您已通過測驗,能在互動式實作環境中應用相關 知識。完成本技能徽章課程及結業評量挑戰 實驗室,即可取得技能徽章並與他人分享。
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.
Complete the introductory Create and Manage Bigtable Instances skill badge to demonstrate skills in the following: creating instances, designing schemas, querying data, and performing administrative tasks in Bigtable including monitoring performance and configuring node autoscaling and replication.
This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.
這堂初級課程將介紹 Google Cloud 的資料分析工作流程,以及用於探索、分析資料並以圖表呈現的工具。您也能學會如何與相關人員分享自己的發現結果。本課程包含個案研究、實作實驗室、講座、測驗和示範,實際展示如何將原始資料集轉化為清晰的資料,進而呈現出能發揮成效的圖表和資訊主頁。無論您是資料領域從業人員、想瞭解如何透過 Google Cloud 取得成功,或有意在職涯中更上一層樓,本課程都能協助您踏出第一步。絕大多數在工作上執行或運用資料分析的學員,都能從本課程受益。
In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.