Zain Bharde
成为会员时间:2023
黄金联赛
14505 积分
成为会员时间:2023
“Google Cloud 基础知识:核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务,并提供重要的资源和政策管理工具。
This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.
In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
完成为 Looker 信息中心和报告准备数据入门级技能徽章课程, 展现您在以下方面的技能:对数据进行过滤、排序和透视;将来自不同 Looker 探索的结果合并; 以及使用函数和运算符构建 Looker 信息中心和报告以用于数据分析和可视化。 技能徽章是由 Google Cloud 颁发的专属数字徽章,旨在认可 您在 Google Cloud 产品与服务方面的熟练度;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,即可获得技能徽章,在您的人际圈中 炫出自己的技能。
This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.