About this Course
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Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 8 hours to complete

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

English

Subtitles: French, Portuguese (Brazilian), German, English, Spanish, Japanese...

Skills you will gain

BigqueryBigtableDataflowPublish–Subscribe Pattern

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 8 hours to complete

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

English

Subtitles: French, Portuguese (Brazilian), German, English, Spanish, Japanese...

Syllabus - What you will learn from this course

Week
1
1 hour to complete

Module 1: Architecture of Streaming Analytics Pipelines

...
5 videos (Total 39 min), 1 reading, 1 quiz
5 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
1 reading
Lab Worksheet10m
1 practice exercise
Module 1 Quiz4m
2 hours to complete

Module 2: Ingesting Variable Volumes

...
4 videos (Total 34 min), 2 quizzes
4 videos
How it works: Topics and Subscriptions14m
Lab Overview34s
Lab demo and review8m
1 practice exercise
Module 2 Quiz8m
2 hours to complete

Module 3: Implementing Streaming Pipelines

...
6 videos (Total 70 min), 2 quizzes
6 videos
Challenges in stream processing14m
Build a stream processing pipeline for live traffic data11m
Handle late data: watermarks, triggers, accumulation14m
Lab overview35s
Lab demo and review15m
1 practice exercise
Module 3 Quiz2m
1 hour to complete

Module 4: Streaming analytics and dashboards

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3 videos (Total 20 min), 2 quizzes
3 videos
Lab overview45s
Lab demo and review5m
1 practice exercise
Module 4 Quiz4m
2 hours to complete

Module 5: Handling Throughput and Latency Requirements

...
8 videos (Total 63 min), 1 reading, 2 quizzes
8 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
1 reading
Cloud Bigtable Streaming10m
1 practice exercise
Module 5 Quiz6m
4.7
108 ReviewsChevron Right

38%

started a new career after completing these courses

37%

got a tangible career benefit from this course

15%

got a pay increase or promotion

Top reviews from Building Resilient Streaming Systems on Google Cloud Platform

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, Big Data, and Machine Learning on GCP 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, Big Data, and Machine Learning on GCP

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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