Google Professional-Data-Engineer日本語 Exam Collection - Google Certified Professional Data Engineer Exam (Professional-Data-Engineer日本語版)

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About Google Professional-Data-Engineer日本語 Exam

Google Cloud Big Data & Machine Learning Fundamentals course

This course is a gateway to introduce you to Google Cloud's big data and different machine learning functions. However, to successfully pass this training, you have to attain one year of experience in SQL, extract transform, data modeling, machine learning, programming in Python, and load activities. So, the objectives of the course are the following:

  • Utilize Cloud SQL & Dataproc to migrate existing MySQL, Pig, Spark, or Hive workloads to Google Cloud
  • Hire BigQuery and Cloud SQL for interactive data analysis
  • Recognize the purpose of the key Big data and Machine Learning products in Google Cloud
  • Create ML models using BigQuery ML, APIs, and AutoML.

Introduction

Data engineers are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. This IT role requires a significant set of technical skills, including a deep knowledge of SQL database design and multiple programming languages They collect, transform, and visualize data. The Data Engineer designs, builds, maintains, and troubleshoots data processing systems with a particular emphasis on the security, reliability, fault-tolerance,scalability, fidelity, and efficiency of such systems.

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Data Engineering on Google Cloud course

It is a 4-day course that gives hands-on experience to the candidates and allows them to build data processing systems on Google Cloud. It will also show you how to design data processing systems, analyze data and build end-to-end data pipelines and machine learning. In order to get a better understanding of the course, you need to complete the big data machine learning course or get equivalent experience. This course also aids you in developing applications using a programming language such as Python and covers the following objective:

  • Influencing unstructured data using ML APIs on Cloud Dataproc
  • Predicting machine models using TensorFlow and Cloud ML
  • Designing and building data processing systems on the Google Cloud Platform
  • Enable insights from streaming data
  • Processing batch and streaming data by using autoscaling data pipelines on Cloud Dataflow

Reference: https://cloud.google.com/certification/data-engineer

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