Data Engineering on Google Cloud Platform

Data Engineering on Google Cloud Platform Specialization

Launch your career in Data Engineering. Deliver business value with big data and machine learning.

About This Specialization

This five-course accelerated specialization is designed for data professionals who are responsible for designing, building, analyzing, and optimizing big data solutions. Through a combination of video lectures, quizzes, and hands-on labs, you'll learn how to carry out serverless data analysis and productionize machine learning models. This specialization is designed to give participants a robust hands-on experience and is primarily lab-focused. Learn how to deliver business value with Big Data and Machine Learning Solutions on Google Cloud Platform. To get up to speed quickly, follow the courses in this specialization. This specialization is unique in that you'll actually get to work within the Google Cloud Platform production environment, develop external applications, and achieve an end-of-specialization certificate. Note for Google Cloud customers and partners: This specialization is the on-demand equivalent to the CPB100 and CPB210 instructor-led training classes. CPB100 is listed as Google Cloud Platform Big Data and Machine Learning Fundamentals and Data Engineering on Google Cloud Platform has been divided into four courses: 1) Leveraging Unstructured Data on Dataproc on Google Cloud Platform, 2) Serverless Data Analysis with Google BigQuery and Cloud Dataflow, 3) Serverless Machine Learning with Tensorflow on Google Cloud Platform, and 4) Building Resilient Streaming Systems on Google Cloud Platform.

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5 courses

Follow the suggested order or choose your own.

Projects

Designed to help you practice and apply the skills you learn.

Certificates

Highlight your new skills on your resume or LinkedIn.

Projects Overview

This specialization incorporates hands-on labs. You will need a Google account (a Gmail account will work just fine) and will be required to sign up for a Google Cloud Platform free trial account. Your free trial is limited to 12 months or $300 worth in credits, whichever is reached first. For this reason, our specialization is designed to be completed within four weeks.

These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google BigQuery, which are used and configured within the Codelabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.

Courses

Intermediate Specialization.: Some related experience required.

COURSE 1
Google Cloud Platform Big Data and Machine Learning Fundamentals
Current session: Sep 18 — Oct 2.
Commitment
1 week of study, 6-10 hours/week
Subtitles
English
About the Course
This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform • Employ BigQuery and Cloud Datalab to carry out interactive data analysis • Choose between Cloud SQL, BigTable and Datastore • Train and use a neural network using TensorFlow • Choose between different data processing products on the Google Cloud Platform Before enrolling in this course, participants should have roughly one (1) year of experience with one or more of the following: • A common query language such as SQL • Extract, transform, load activities • Data modeling • Machine learning and/or statistics • Programming in Python Google Account Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China). • There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602 • More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
You can choose to take this course only. Learn more.
COURSE 2
Leveraging Unstructured Data with Cloud Dataproc on Google Cloud Platform
Current session: Sep 18 — Oct 2.
Commitment
1 week of study, 5-7 hours/week
Subtitles
English
About the Course
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
You can choose to take this course only. Learn more.
COURSE 3
Serverless Data Analysis with Google BigQuery and Cloud Dataflow
Current session: Sep 18 — Oct 2.
Commitment
1 week of study, 6-8 hours/week
Subtitles
English
About the Course
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 Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China). • There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602 • More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
You can choose to take this course only. Learn more.
COURSE 4
Serverless Machine Learning with Tensorflow on Google Cloud Platform
Upcoming session: Sep 25 — Oct 9.
Commitment
1 week of study, 8-12 hours/week
Subtitles
English
About the Course
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 Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China). • There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as "business" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602 • More Google Cloud Platform free trial FAQs are available at: https://cloud.google.com/free-trial/
You can choose to take this course only. Learn more.
COURSE 5
Building Resilient Streaming Systems on Google Cloud Platform
Current session: Sep 18 — Oct 2.
Commitment
1 week of study, 6-8 hours/week
Subtitles
English
About the Course
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
You can choose to take this course only. Learn more.

Creators

The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way.
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