- Google Cloud
- Machine Learning
- Feature Engineering
- Tensorflow
- Cloud Computing
- Bigquery
- Google Cloud Platform
- Application Programming Interfaces (API)
- Inclusive ML
- Data Cleansing
- Python Programming
- Build Input Data Pipeline
准备考取 Google Cloud 认证:机器学习工程师 专业证书
Advance your career as a Cloud ML Engineer
提供方
您将学到的内容有
Learn the skills needed to be successful in a machine learning engineering role
Prepare for the Google Cloud Professional Machine Learning Engineer certification exam
Understand how to design, build, productionalize ML models to solve business challenges using Google Cloud technologies
Understand the purpose of the Professional Machine Learning Engineer certification and its relationship to other Google Cloud certifications
您将获得的技能

关于此 专业证书
应用的学习项目
This specialization incorporates hands-on labs using Google's Qwiklabs platform.
These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud Platform products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.
We recommend participants have data engineering or programming experience and are interested in learning how to apply machine learning in practice
We recommend participants have data engineering or programming experience and are interested in learning how to apply machine learning in practice
专业证书是什么?
塑造技能,做好工作准备
无论您是想开始新的职业生涯,还是改变目前职业,Coursera 专业证书都能帮您为开始工作做好准备。选择最适合的时间和地点,自行安排学习进度。立即注册,探索新的职业道路,可免费试用 7 天。您可以随时暂停学习或结束订阅。
实践项目
将您的技能应用到实践项目,并丰富您的简历内容,进而向潜在雇主展示您已为开始工作做好准备。您需要成功完成项目以获得证书。
获得职业证书
当完后计划中的所有课程后,您将获得一张证书。您可以将其在专业网络上分享,并获得使用职业支持资源的权限,这能够为您开启职业生涯提供助力。许多招聘合作伙伴认可我们的许多专业证书,并且我们还有许多合作伙伴可以帮助您准备认证考试。您可以在适用的各个专业证书页面上找到更多信息。

此专业证书包含 9 门课程
Google Cloud Big Data and Machine Learning Fundamentals
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
How Google does Machine Learning
What are best practices for implementing machine learning on Google Cloud? What is Vertex AI and how can you use the platform to quickly build, train, and deploy AutoML machine learning models without writing a single line of code? What is machine learning, and what kinds of problems can it solve?
Launching into Machine Learning
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.
TensorFlow on Google Cloud
This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.
提供方

Google 云端平台
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
常见问题
退款政策是如何规定的?
我可以只注册一门课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程需要多长时间?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
还有其他问题吗?请访问 学生帮助中心。