This program provides the skills you need to advance your career in data engineering and recommends training to support your preparation for the industry-recognized Google Cloud Professional Data Engineer certification. Through a combination of presentations, demos, and labs, you will enable data-driven decision making by collecting, transforming, and publishing data; and you'll gain real world experience through a number of hands-on Qwiklabs projects. You'll also have the opportunity to practice key job skills, including designing, building, and running data processing systems; and operationalizing machine-learning models. Upon successful completion of this program, you will earn a certificate of completion to share with your professional network and potential employers. If you would like to become Google Cloud certified and demonstrate your proficiency to design and build data processing systems and operationalize machine learning models on Google Cloud Platform, you will need to register for, and pass the official Google Cloud certification exam. You can find more details on how to register and additional resources to support your preparation at cloud.google.com/certifications.
Data Engineering with Google Cloud プロフェッショナル認定
Advance your career in data engineering
提供：
このプロフェッショナル認定について
学習内容
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
100%オンラインコース
フレキシブルなスケジュール
中級レベル
You should have basic proficiency with a common query language such as SQL; experience developing applications using common programming languages.
英語
プロフェッショナル認定とは何ですか？
仕事の準備ができるスキルを構築する
新しいキャリアを始めようとしている方も、現在のキャリアを変更しようとする方も、Coursera（コーセラ）のプロフェッショナル認定は、仕事の準備をするのに役立ちます。自分のペースで、いつでもどこでも、最も便利な場所で学びましょう。今すぐ登録して、7日間の無料トライアルで新しいキャリアパスを探索してください。学習を一時停止したり、サブスクリプションをいつでも終了することができます。
実践型プロジェクト
実践型プロジェクトでスキルを活用し、潜在的な雇用主に仕事の準備ができていることを示すポートフォリオを構築します。認定証を獲得するには、成功裏にプロジェクトを終了させる必要があります。
キャリアに役立つ資格を取得
プログラムのすべてのコースを修了すると、認定資格を取得してプロフェッショナルのネットワークと共有し、キャリアサポートリソースへのアクセスをロック解除して、新しいキャリアを開始できます。多くのプロフェッショナル認定にはプロフェッショナル認定を認める採用パートナーがいます。他の認定は、認定試験の準備に役立ちます。それぞれのプロフェッショナル認定ページで詳細を確認することができます。
このプロフェッショナル認定には6コースあります。
Google Cloud Platform Big Data and Machine Learning Fundamentals
This 2-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • Google services are currently unavailable in China.
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. Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud Platform. Cloud Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Cloud Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud Platform using QwikLabs.
講師
Google Cloud Training
受講者524,966 名
186 コースGoogle Cloudについて
よくある質問
Coursera Plusとは何ですか？また返金ポリシーはどのようなものですか？
返金ポリシーについて教えてください。
1つのコースだけに登録することは可能ですか？
はい。まず始めに興味のあるコースカードをクリックして登録します。コースに登録して修了することによって、共有できる修了証を取得するか、無料でコースを聴講してコースの教材を確認することができます。修了証の一部であるコースにサブスクライブすると、修了証全体に自動的にサブスクライブされます。進捗を追跡するには、受講生のダッシュボードにアクセスしてください。
このコースは100%オンラインで提供されますか？実際に出席する必要のあるクラスはありますか？
このコースは完全にオンラインで提供されているため、実際に教室に出席する必要はありません。Webまたはモバイル機器からいつでもどこからでも講義、学習用教材、課題にアクセスできます。
How long does it take to complete the Professional Certificate?
This Professional Certificate is designed to be completed in one and a half months at 5 hours per week.
What background knowledge is necessary?
To get the most out of this program, learners should have basic proficiency with a common query language such as SQL; experience developing applications using a common programming language such as Python; experience with data modeling, extract, transform, load activities ; and familiarity with machine learning and/or statistics.
Do I need to take the courses in a specific order?
We strongly recommend you take these courses in order, beginning with Big Data and Machine Learning Fundamentals. This is especially important when completing the Qwiklabs projects, as these hands-on labs build upon the work you complete in preceding courses.
さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。
