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所在平台: Udemy |
课程主页: https://www.udemy.com/course/google-certified-professional-machine-learning/
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课程名称：谷歌专业机器学习工程师 2025 首次尝试！ 课程概述：通过模拟测试成为谷歌云认证的专业机器学习工程师！本课程提供218道类似真实考试的问题及答案，每个正确答案都附有详细解释，确保您深入理解相关概念。而即使是错误答案，也会提供详尽的解释，使每次失误成为宝贵的学习机会。此外，我们还推荐外部参考资料，帮助您进一步拓宽对覆盖主题的理解。 作为一名专业机器学习工程师，您将利用谷歌云技术和经过验证的模型与技术来构建、评估、生产化和优化机器学习模型。这一职位需要处理大量复杂数据集，并创建可重复使用的代码。工程师在整个模型开发过程中将负责任的人工智能和公平性纳入考虑，并与其他职位紧密合作，以确保机器学习应用的长期成功。 机器学习工程师应具备扎实的编程技能，熟悉数据平台和分布式数据处理工具，并在模型架构、数据和机器学习管道创建以及指标解读等领域表现出色。此外，工程师需了解MLOps的基础概念、应用开发、基础设施管理、数据工程和数据治理，使机器学习在整个组织中具有可及性。 课程的内容包括如何设计和创建可扩展、性能优越的解决方案，通过培训、重训、部署、调度、监控和改进模型来实现。专业机器学习工程师考试评估您的能力，包括： - 设计低代码的机器学习解决方案 - 在团队内外协作管理数据和模型 - 将原型扩展为机器学习模型 - 服务和扩展模型 - 自动化和协调机器学习管道 目标受众：此课程面向学生、顾问、软件开发人员、IT主管、IT经理、IT团队领导和IT专业人员。 认证考试信息： - 考试时长：2小时 - 语言：英语 - 考试形式：50-60道多项选择和多选题
SIMULATORS 2025!!. Become a Google Cloud Certified Professional Machine Learning Engineer in First Attempt. This course consists of 218 questions and answers like the real exam!!. Every correct answer comes with a thorough explanation to ensure you understand the concept in-depth.Even incorrect answers are accompanied by detailed explanations, turning each error into a valuable learning opportunityExpand your understanding with recommended external references. We provide additional resources for you to delve even deeper into the covered topics.A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes ML models by using Google Cloud technologies and knowledge of proven models and techniques. The ML Engineer handles large, complex datasets and creates repeatable, reusable code.The ML Engineer considers responsible AI and fairness throughout the ML model development process, and collaborates closely with other job roles to ensure long-term success of ML-based applications. The ML Engineer has strong programming skills and experience with data platforms and distributed data processing tools. The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, and metrics interpretation.The ML Engineer is familiar with foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance. The ML Engineer makes ML accessible and enables teams across the organization. By training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable, performant solutions.The Professional Machine Learning Engineer exam assesses your ability to:Architect low-code ML solutionsCollaborate within and across teams to manage data and modelsScale prototypes into ML modelsServe and scale modelsAutomate and orchestrate ML pipelinesAudience Profile:The target audience includes:- Students- Consultants- Software Developers- IT Directors- IT Managers- IT Team Leaders- IT ProfessionalsAbout this certification exam:Length: 2 hoursLanguages: English,Exam format: 50-60 multiple choice and multiple select questions
