Профессиональная сертификация 'Data Engineering with Google Cloud'
Advance your career in data engineering
от партнера
Чему вы научитесь
Learn the skills needed to be successful in a data engineer role
Prepare for the Professional Data Engineer certification
Learn about the infrastructure and platform services provided by Google Cloud Platform
Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.
Приобретаемые навыки
Профессиональная сертификация: общие сведения
Проект прикладного обучения
This Professional Certificate incorporates hands-on labs using our 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 BigQuery, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
Профессиональная сертификация включает несколько курсов: 6
Google Cloud Platform Big Data and Machine Learning Fundamentals
This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud.
Modernizing Data Lakes and Data Warehouses with GCP
The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
Building Batch Data Pipelines on GCP
Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud Platform for data transformation including BigQuery, executing Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Cloud Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud Platform using QwikLabs.
Building Resilient Streaming Analytics Systems on GCP
*Note: this is a new course with updated content from what you may have seen in the previous version of this Specialization.
от партнера

Google Cloud
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.
Часто задаваемые вопросы
Получу ли я зачеты в университете за прохождение специализации?
Can I just enroll in a single course?
Можно ли зарегистрироваться только на один курс?
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
Остались вопросы? Посетите Центр поддержки учащихся.