M T
회원 가입일: 2021
브론즈 리그
6000포인트
회원 가입일: 2021
생성형 AI란 무엇이고 어떻게 사용하며 전통적인 머신러닝 방법과는 어떻게 다른지 설명하는 입문용 마이크로 학습 과정입니다. 직접 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.
Ready for this week's Trivia? Complete all the labs and add this premium badge to your profile. Get credits worth $25 to continue your cloud learning journey. Hurry and join today as the game closes soon. Access code: 1q-trivia-422.
Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
Welcome to the Learn To Earn Cloud Challenge data plus track! "The Google Cloud Certified Professional Data Engineer certification is associated with the highest paying salary in IT," according to the most recent Global Knowledge skills and salary report (published August 2021). Complete this game to earn the Data Plus game badge, and be eligible for a +bonus+ prize in the Learn to Earn Cloud Challenge. See "what's next" below for details and requirements; you’ll need to earn at least 2 additional challenge badges to qualify. You'll learn next-level data skills to add to your resume. Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
중급 BigQuery로 데이터 웨어하우스 빌드 기술 배지를 완료하여 데이터를 조인하여 새 테이블 만들기, 조인 관련 문제 해결, 합집합으로 데이터 추가, 날짜로 파티션을 나눈 테이블 만들기, BigQuery에서 JSON, 배열, 구조체 작업하기와 관련된 기술 역량을 입증하세요.
Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
중급 BigQuery ML로 ML 모델 만들기 기술 배지 과정을 완료하면 BigQuery ML로 머신러닝 모델을 만들고 평가하여 데이터 예측을 수행하는 기술 역량을 입증할 수 있습니다.
Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
초급 BigQuery 데이터에서 인사이트 도출 기술 배지 과정을 완료하여 SQL 쿼리 작성, 공개 테이블 쿼리, BigQuery로 샘플 데이터 로드, BigQuery의 쿼리 검사기를 통한 일반적인 문법 오류 문제 해결, BigQuery 데이터를 연결해 Looker Studio에서 보고서를 생성하는 작업과 관련된 기술 역량을 입증하세요.
초급 Looker 대시보드 및 보고서를 위해 데이터 준비하기 기술 배지 과정을 완료하면 데이터를 필터링, 정렬, 피벗팅하고, 다른 Looker Explore의 결과를 병합하고, 함수 및 연산자를 사용해 데이터 분석 및 시각화를 위한 Looker 대시보드 및 보고서를 빌드하는 기술 역량을 입증할 수 있습니다.
Welcome to the Learn To Earn Cloud Challenge security track! These eight labs give you the keys to understanding GCP's powerful security suite. At the end of each lab, you'll have hands-on experience with securing your cloud. Complete this game to earn the Security game badge, and you'll be one step closer to collecting all four badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge data track! These eight labs give you a deep dive into GCP's data universe. At the end of each lab, you'll have another in-demand skill to add to your list. Complete this game to earn the Data game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge architecture track! These eight labs give you a blueprint of GCP's building blocks. At the end of each lab, you'll have hands-on experience with another tool or service to add to your resume. Complete this game to earn the Architecture game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
Welcome to the Learn To Earn Cloud Challenge! These eight labs give you a quick hands-on introduction to eight different GCP tools and services. At the end of each lab, you'll have another skill to add to your list. Complete this game to earn the Essentials game badge, and you'll be one step closer to collecting all four Learn to Earn Cloud Challenge badges (see "what's next" below for more information). Race the clock to increase your score and watch your name rise on the leaderboard. Good luck!
이 초급 과정에서는 Google Cloud의 기본 도구 및 서비스를 직접 사용해 보는 실무형 실습을 진행합니다. 선택사항으로 제공되는 동영상에서는 실습에서 다룬 개념을 자세히 살펴보고 복습합니다. Google Cloud 필수 정보는 Google Cloud 학습자에게 추천되는 첫 번째 과정입니다. 클라우드에 대한 사전 지식이 거의 없거나 전혀 없더라도 첫 Google Cloud 프로젝트에 적용할 수 있는 실무 경험을 쌓을 수 있습니다. Cloud Shell 명령어 작성, 첫 번째 가상 머신 배포, Kubernetes Engine에서의 애플리케이션 실행, 부하 분산 등 Google Cloud 필수 정보에서는 플랫폼의 기본 기능을 소개합니다.