Google Cloud Certified Professional Data Engineer

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Udemy based on 238 ratings

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Overview

This certification-focused course prepares learners to become a Google Cloud Certified Professional Data Engineer. It covers core topics including data pipeline design, ETL processing, data warehousing with Big Query, machine learning model deployment, and real-time data analysis. Youâll work with tools like Dataflow, Pub/Sub, Dataproc, and Cloud Composer, gaining hands-on experience through labs and projects. The course also covers security, cost optimization, and scalability within GCPâs architecture. Ideal for data engineers, cloud architects, and analytics professionals, it equips you with...

Syllabus

Data Engineering Concepts
Google Cloud Storage - Solid State Drive in the Cloud
Migrating Data - Google Data Transfer Service, gsutil, Transfer Appliance
Cloud SQL - MySQL, PostgreSQL, Microsoft SQL Server in the Cloud
Cloud Spanner - Horizontally Scalable Distributed Multi Region SQL Database
Cloud Dataflow - Managed Apache Beam Service for Data Processing, Transformation
Cloud Dataproc - Managed Apache Hadoop, Spark in the Cloud
Cloud Pub/Sub - Publisher Subscriber Architecture based Solution for Streaming
Cloud BigQuery - Ad Hoc Analytical SQL Query Solution for Massive Datasets
BigQuery ML - Machine Learning Model Building Directly onto BigQuery using SQL
Cloud BigTable - NoSQL Massively Distributed Extremely Performant Database
Cloud Composer - Managed Apache Airflow Service for Workflow Orchestration
Cloud Firestore - NoSQL JSON Based Document Database - Similar to MongoDB
Data Studio - Visualisation, 100% Web Based, No Programming, Reports, Dashboards
Cloud DataPrep - Data Preparation using point and clicks on Web - No Programming
Cloud Data Fusion - Point & Click Solution for Creating Data Pipelines & Connect
Cloud Data Catalog - Metadata Management for Data Movement, Lineage, Discovery
Cloud Memorystore - Managed Redis, Memcached Service on Cloud for Key Value Data
Cloud Data Loss Prevention (DLP) Service - redact, mask, tokenize & transform
Machine Learning Concepts
Google Cloud Machine Learning Services and APIs
Practice Questions and Answers with Explanations
Big Data Technologies - Optional Learning