About this Course
4.7
833 ratings
65 reviews
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 7 hours to complete

Suggested: 1 week of study, 6-8 hours/week...
Available languages

English

Subtitles: English

Skills you will gain

BigqueryBigtableDataflowPublish–Subscribe Pattern
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 7 hours to complete

Suggested: 1 week of study, 6-8 hours/week...
Available languages

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
Hours to complete
1 hour to complete

Module 1: Architecture of Streaming Analytics Pipelines

...
Reading
5 videos (Total 39 min), 1 reading, 1 quiz
Video5 videos
Challenge #1: Variable volumes require ability of ingest to scale and be fault-tolerant4m
Challenge #2 : Latency is to be expected5m
Challenge #3 : Need instant insights6m
Discuss some streaming scenarios8m
Reading1 reading
Lab Worksheet10m
Quiz1 practice exercise
Module 1 Quiz4m
Hours to complete
2 hours to complete

Module 2: Ingesting Variable Volumes

...
Reading
4 videos (Total 34 min), 2 quizzes
Video4 videos
How it works: Topics and Subscriptions14m
Lab Overviewm
Lab demo and review8m
Quiz1 practice exercise
Module 2 Quiz8m
Hours to complete
2 hours to complete

Module 3: Implementing Streaming Pipelines

...
Reading
6 videos (Total 70 min), 2 quizzes
Video6 videos
Challenges in stream processing14m
Build a stream processing pipeline for live traffic data11m
Handle late data: watermarks, triggers, accumulation14m
Lab overviewm
Lab demo and review15m
Quiz1 practice exercise
Module 3 Quiz2m
Hours to complete
1 hour to complete

Module 4: Streaming analytics and dashboards

...
Reading
3 videos (Total 20 min), 2 quizzes
Video3 videos
Lab overviewm
Lab demo and review5m
Quiz1 practice exercise
Module 4 Quiz4m
Hours to complete
2 hours to complete

Module 5: Handling Throughput and Latency Requirements

...
Reading
8 videos (Total 63 min), 2 quizzes
Video8 videos
Bigtable: big, fast, autoscaling NoSQL4m
Ingesting into Bigtable4m
Designing for Bigtable23m
Streaming into Bigtable1m
Lab demo and review4m
Performance considerations6m
Summary of Data Engineering on GCP Specialization8m
Quiz1 practice exercise
Module 5 Quiz6m
4.7
65 ReviewsChevron Right
Career direction

67%

started a new career after completing these courses
Career Benefit

83%

got a tangible career benefit from this course
Career promotion

17%

got a pay increase or promotion

Top Reviews

By PGAug 25th 2018

This course was very helpful to understand how to built high throughput streaming work flows on google cloud. It described in detail how to model big table for efficient application.

By CCAug 19th 2017

Course gives nice overview of Bigtable, when to use it compared to bigquery. flowchart describing the when to use which product is really helpful. Thanks Lak for the course.

About Google Cloud

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

About the Data Engineering on Google Cloud Platform Specialization

This five-week, accelerated online specialization provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data. This course teaches the following skills: • Design and build data processing systems on Google Cloud Platform • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow • Derive business insights from extremely large datasets using Google BigQuery • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML • Enable instant insights from streaming data This class is intended for developers who are responsible for: • Extracting, Loading, Transforming, cleaning, and validating data • Designing pipelines and architectures for data processing • Creating and maintaining machine learning and statistical models • Querying datasets, visualizing query results and creating reports >>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...
Data Engineering on Google Cloud Platform

Frequently Asked Questions

  • Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

  • If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

  • Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

  • If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

  • This course is one of a few offered on Coursera that are currently available only to learners who have paid or received financial aid, when available.

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