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所在平台: Udemy |
课程主页: https://www.udemy.com/course/google-cloud-certified-professional-data-engineer-practice-tests-2023/
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课程名称：GCP认证数据工程师 - 2023年实践测试 课程概述： 本课程专为准备谷歌云专业数据工程师考试的学员设计，旨在提供考试相关的问题与答案，以帮助考生测试和增强对考试目标的理解与掌握。数据工程师的主要职责是收集、转化和发布数据，从而支持基于数据的决策。获得谷歌云认证的专业数据工程师证书将有助于您在谷歌云行业追求更好的职涯发展。为了顺利通过考试，您需要通过多次实践测试来持续学习和复习。 该课程包含超过250道可能出现在谷歌云专业数据工程师考试中的问题，部分问题具有自明性，必要时附有解释。通过这些实践测试，学员可以验证自己的熟练程度，并增强获得认证所需的信心。本测试的重点在于测试学员对以下概念的掌握能力： - 设计数据处理系统 - 构建和运营数据处理系统 - 实现机器学习模型的运营 - 确保解决方案的质量 测评技能包括： - 选择适当的存储系统，包括关系型、NoSQL和分析型数据库 - 在生产环境中部署机器学习模型 - 设计可扩展、可靠的分布式数据密集型应用 - 评估和改进机器学习模型的质量 - 构建可扩展、可靠的数据管道 - 将多种机器学习技术应用于不同的用例 - 监控数据管道和机器学习模型 - 将数据仓库从本地迁移至谷歌云 - 理解机器学习的基本概念，如反向传播、特征工程、过拟合与欠拟合 可否重复参加实践测试？每个实践测试可以多次参加，完成测试后会发布您的最终结果。每次参加测试时，问题和答案的顺序会被随机打乱。
Are you looking for the Google Cloud Professional Data Engineer Exam Questions? The questions and answers provided here test and enhance your knowledge of the exam objectives.A professional Data Engineer collects, transforms, and publishes the data, thereby enabling data-driven decision making. Earning a Google Cloud Certified Professional Data Engineer certification may help you in pursuing a better career in the Google cloud industry. To pass the actual exam, you have to spend more time on learning & re-learning through multiple practice tests.This course is in the form of practice tests and consists of over 250 questions that may appear during the Google Cloud Professional Data Engineer exam. Some questions are self-explanatory. Where necessary, explanations are added to the questions. This course allows you to confirm your proficiency and give you the confidence you need to earn a Google Cloud Professional Data Engineer certification.This practice test measures your ability to master the following concepts: Designing data processing systemsBuilding and operationalizing data processing systemsOperationalizing machine learning modelsEnsuring solution qualitySkills measured:Choose appropriate storage systems, including relational, NoSQL and analytical databasesDeploy machine learning models in productionDesign scalable, resilient distributed data intensive applicationsEvaluate and improve the quality of machine learning modelsBuild scalable, reliable data pipelinesApply multiple types of machine learning techniques to different use casesMonitor data pipelines and machine learning modelsMigrate data warehouse from on-premises to Google CloudGrasp fundamental concepts in machine learning, such as backpropagation, feature engineering, overfitting and underfitting.Can I take the practice test more than once?You can take each practical test multiple times. After completing the practice test, your final result will be published. Each time you take the test, the order of questions and answers is randomized.
