Preparing for Google Cloud Certification: Cloud Data Engineer

Overview

Syllabus

Courses

• 5 reviews

  9 hours 29 minutes

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  This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
• 0 reviews

  1 week

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  This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models.
  
  OBJECTIVES
  
  This course teaches participants the following skills:
  
  ● Identify use cases for machine learning
  
  ● Build an ML model using TensorFlow
  
  ● Build scalable, deployable ML models using Cloud ML
  
  ● Know the importance of preprocessing and combining features
  
  ● Incorporate advanced ML concepts into their models
  
  ● Productionize trained ML models
  
  
  PREREQUISITES
  
  To get the most of out of this course, participants should have:
  
  ● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience
  
  ● Basic proficiency with common query language such as SQL
  
  ● Experience with data modeling, extract, transform, load activities
  
  ● Developing applications using a common programming language such Python
  
  ● Familiarity with Machine Learning and/or statistics
  
  Google Account Notes:
  • Google services are currently unavailable in China.
• 0 reviews

  4 hours 51 minutes

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  This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
• 0 reviews

  1 week, 6-8 hours a week, 6-8 hours a week

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  This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of instructor-led presentations, demonstrations, and hands-on labs, students learn how to carry out no-ops data warehousing, analysis and pipeline processing.
  
  Prerequisites:
  • Google Cloud Platform Big Data and Machine Learning Fundamentals
  • Experience using a SQL-like query language to analyze data
  • Knowledge of either Python or Java
  
  Google Account Notes:
  • Google services are currently unavailable in China.
• 0 reviews

  10 hours

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  Este curso rápido sob demanda tem uma semana de duração e é baseado no Google Cloud Platform Big Data and Machine Learning Fundamentals. Por meio de videoaulas, demonstrações e laboratórios práticos, os participantes aprenderão a criar pipelines de dados de streaming usando o Google Cloud Pub/Sub e o Dataflow para a tomada de decisões em tempo real. Você também aprenderá a criar painéis para renderizar respostas personalizadas para vários tipos de público das partes interessadas. Pré-requisitos: • Noções básicas de Big Data e Machine Learning do Google Cloud Platform (ou experiência equivalente) • Conhecimento de Java Objetivos: • Entender os casos de uso para análise de streaming em tempo real • Usar o serviço de mensagens assíncronas do Google Cloud Pub/Sub para gerenciar eventos de dados • Criar pipelines de streaming e executar transformações • Conhecer os dois lados de um pipeline de streaming: produção e consumo • Interoperar o Dataflow, o BigQuery e o Cloud Pub/Sub para streaming e análise em tempo real
• 0 reviews

  1 week, 5-7 hours a week, 5-7 hours a week

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  This 1-week, accelerated course builds upon previous courses in the Data Engineering on Google Cloud Platform specialization. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to create and manage computing clusters to run Hadoop, Spark, Pig and/or Hive jobs on Google Cloud Platform. You will also learn how to access various cloud storage options from their compute clusters and integrate Google’s machine learning capabilities into their analytics programs.
  
  In the hands-on labs, you will create and manage Dataproc Clusters using the Web Console and the CLI, and use cluster to run Spark and Pig jobs. You will then create iPython notebooks that integrate with BigQuery and storage and utilize Spark. Finally, you integrate the machine learning APIs into your data analysis.
  
  Pre-requisites
  • Google Cloud Platform Big Data & Machine Learning Fundamentals (or equivalent experience)
  • Some knowledge of Python

Taught by

Google Cloud Training