Preparing for Google Cloud Certification: Cloud Data Engr
Google Cloud via Coursera Professional Certificate
Overview
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The Google Cloud Professional Data Engineer Certification Program is a comprehensive program that provides the skills you need to advance your career and provides training to help you prepare for the industry-recognized Google Cloud Professional Data Engineer Certification exam administered by Google Cloud.
Recognized as the #1 top-paying certification in 2021 by Global Knowledge, this program is specifically designed for those aspiring to advance in the thriving field of data engineering. 87% of Google Cloud certified users feel more confident in their cloud skills.
In this program, you will learn about the fundamental principles and applications of Big Data and Machine Learning products within Google Cloud. Master how to use BigQuery for interactive data analysis, apply Cloud SQL and Dataproc for migrating existing MySQL and Hadoop/Pig/Spark/Hive tasks to Google Cloud, and differentiate between various data processing products on Google Cloud. You will have the opportunity to comprehend theoretical knowledge fully and apply it in practical situations, making use of Google Cloud Platform's vast range of tools for Real Time Data, Dataflow, and TensorFlow.
Syllabus
- Course 1: Preparing for your Professional Data Engineer Journey
Courses
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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. -
This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn how to build streaming data pipelines using Google Cloud Pub/Sub and Dataflow to enable real-time decision making. You will also learn how to build dashboards to render tailored output for various stakeholder audience.
Prerequisites:
• Google Cloud Platform Big Data and Machine Learning Fundamentals (or equivalent experience)
• Some knowledge of Java
Objectives:
• Understand use-cases for real-time streaming analytics
• Use Google Cloud PubSub asynchronous messaging service to manage data events
• Write streaming pipelines and run transformations where necessary
• Get familiar with both sides of a streaming pipeline: production and consumption
• Interoperate Dataflow, BigQuery and Cloud Pub/Sub for real-time streaming and analysis -
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.
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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. -
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