Building Resilient Streaming Systems on Google Cloud Platform
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Data Engineering, Big Data, and Machine Learning on GCP,
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
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| Rating | 4.4★ based on 158 ratings |
|---|---|
| Length | 2 weeks |
| Effort | 1 week of study, 6-8 hours/week |
| Starts | Jan 20 (223 weeks ago) |
| Cost | $50 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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What people are saying
data engineer
This course gives you the tool to start the long journey in the data engineer path.
There is promise of preparing to Data Engineer Cert, but the course just skims most of the topics, missing a lot others entirely.
In some cases the mandatory Qwiklab labs do not work, and in these situations in particular they don't provide value in reinforcing what is presented in the lectures - and ultimately what you need to know to pass the GCP data engineer certification exam.
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google cloud
Among other things, this certainly makes a strong case for Google Cloud as a highly developer friendly cloud offering.
Some of the questions in the practice exam imply the student has taken Google Cloud Architect certification to cover topics omitted from the Data Engineer course given here.
I recommend this course to learn the fundamentals of Building Resilient Streaming Systems on Google Cloud Platform Very useful.
This course was very helpful to understand how to built high throughput streaming work flows on google cloud.
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streaming systems
Great exercises and a solid background on how to build resilient streaming systems with GCP good Un curso maravilloso.
Cover products in streaming systems.
Great Interacting with streaming systems I have gained some good amount knowledge on GCP with respect to Machine learning and stream data processing.
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data engineering
It teaches the basics but I am not convinced this course prepares the student for the Data Engineering Google Certification.
Great course, and an excellent topic in the Big Data Engineering on GCP.
BTW great source of information about how to do data engineering on GCP.
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very nice
Very nice content and the teacher is amazing, legendary but code labs have problem with source code and should be updated and quiz are very dumb, because this 4 stars is fine and fare.
Very nice course, really liked the hands on labs Course gives nice overview of Bigtable, when to use it compared to bigquery.
Very Nice!
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very interesting
Very interesting.
Very Good content... Good good Very interesting!!
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for example
For example, in the practice exam there are questions on topics that are not covered in this course.
For example, IAM, Dataprep, Transfer Appliance, Storage Transfer Service, Cloud Bigtable cbt tool, Snapshots and Encryption.
For example, the explanation for DataFlow watermark: "DataFlow then tracks whether that window is complete or not.
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la plataforma
Nice Creo que hacen falta ejercicios de programación en la plataforma de google desarrollados por el alumno.
Estos cursos permiten incursionar en la plataforma Google Cloud, es básico y hace falta pasar más tiempo con la plataforma y crear un proyecto grande, pero para empezar está bastante bien.
talking about
The introduction was "So when we talk about scaling here, we're essentially talking about being able to deal with faults, as clients and servers and storage systems ,etc., fail unexpectedly.
It seems the speaker was talking about fault tolerance.
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Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
IT Support Agent @ Google [X] 3 $47k
Google Specialist Contractor $47k
Google Cloud Developer $51k
Google Specialist Manager $54k
Google Cloud Engineer $57k
Google Cloud Architect $70k
Content Specialist for Google Play (@Google) $70k
Google Cloud Platform & Mobile Apps Specialist $75k
Designer at Google $77k
Curriculum Developer, Google Cloud $102k
Head of Scaled Engineering Support, Google Cloud $108k
Head of Alliance Partnerships, Google Cloud Go-to-Market Partnerships $132k
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| Rating | 4.4★ based on 158 ratings |
|---|---|
| Length | 2 weeks |
| Effort | 1 week of study, 6-8 hours/week |
| Starts | Jan 20 (223 weeks ago) |
| Cost | $50 |
| From | Google Cloud via Coursera |
| Instructor | Google Cloud Training |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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