Google Cloud Professional Data Engineer Certification Training
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Google Cloud Professional Data Engineer Certification Training

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Learn the skills required to pass the Google Cloud Professional Data Engineer Certification exam. Master cloud data engineering concepts like data modeling, processing, security, and more with hands-on training.

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Overview

The Google Cloud Professional Data Engineer Certification Training equips you with the expertise to design, build, and manage robust data systems on Google Cloud. This comprehensive program covers essential topics such as data modeling, real-time data processing, data security, and machine learning integrations. With hands-on projects, interactive labs, and expert guidance, this training ensures you're prepared to ace the certification exam and succeed as a certified Data Engineer. Unlock career opportunities in cloud computing with this in-demand certification.

Key Features

  • Comprehensive Curriculum
  • Expert Instructors
  • Industry-Relevant Projects
  • Certification Assistance

Curriculum

Study Plan

1Module 1: Preparing for the Google Cloud Professional Data Engineer
  • Designing Data Processing Systems
  • Building and Operationalizing Data Processing Systems
  • Operationalizing Machine Learning Models
  • Security, Policy, and Reliability
2Module 2: Preparing for the Google Cloud Professional Data Engineer
  • Introduction
  • Big Data and Machine Learning on Google Cloud
  • Data Engineering for Streaming Data
  • Big Data with BigQuery
  • Machine Learning Options on Google Cloud
  • The Machine Learning Workflow with Vertex AI
3Module 3: Modernizing Data Lakes and Data Warehouses with Google Cloud
  • Introduction
  • Introduction to Data Engineering
  • Building a Data Lake
  • Building a Data Warehouse
4Module 4: Building Batch Data Pipelines on Google Cloud
  • Introduction to Building BatchData Pipelines
  • Executing Spark on Dataproc
  • Serverless Data Processing with Dataflow
  • Manage Data Pipelines with Cloud Data Fusion and Cloud Composer
5Module 5: Building Resilient Streaming Analytics Systems on Google Cloud
  • Introduction to Processing Streaming Data
  • Serverless Messaging with Pub/Sub
  • Dataflow Streaming Features
  • High-Throughput BigQuery and Bigtable Streaming Features
  • Advanced BigQuery Functionality and Performance
6Module 6: Smart Analytics, Machine Learning, and AI on Google Cloud
  • Introduction to Analytics and AI
  • Prebuilt ML Model APIs for Unstructured Data
  • Big Data Analytics with Notebooks
  • Production ML Pipelines with Kubeflow
  • Custom Model building with SQL in BigQuery ML
  • Custom Model Building with AutoML

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