ZP
Very useful to know. I found this course very interesting.

It is becoming harder and harder to maintain a technology stack that can keep up with the growing demands of a data-driven business. Every Big Data practitioner is familiar with the three V’s of Big Data: volume, velocity, and variety. What if there was a scale-proof technology that was designed to meet these demands? Enter Google Cloud Dataflow. Google Cloud Dataflow simplifies data processing by unifying batch & stream processing and providing a serverless experience that allows users to focus on analytics, not infrastructure. This specialization is intended for customers & partners that are looking to further their understanding of Dataflow to advance their data processing applications. This specialization contains three courses: Foundations, which explains how Apache Beam and Dataflow work together to meet your data processing needs without the risk of vendor lock-in Develop Pipelines, which covers how you convert our business logic into data processing applications that can run on Dataflow Operations, which reviews the most important lessons for operating a data application on Dataflow, including monitoring, troubleshooting, testing, and reliability.

ZP
Very useful to know. I found this course very interesting.
AV
Found this course very helpful while learning developing pipelines in gcp using dataflow-beam.
RT
Good intermediate course covering the big picture about how to develop data platforms using GCP and Dataflow.
SR
It would be better having detailed explanation of concepts for very beginners. This is a great course. Having detailed information will help learners learn quickly
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Easy and quick
It would be better having detailed explanation of concepts for very beginners. This is a great course. Having detailed information will help learners learn quickly
very good
Too much technical explanation without useful implementation details. All of the labs are cut-and-paste instructions into the terminal without sufficient explanation of what you're doing on your own. You can obviously go back and explore these things on your own, but I feel like this is important for the course itself.
It's plain boring without appropriate information what is happening inside. Slides are terrible.
Basically course doesn't teach you anything useful and simply fills you with information that can be read in the Dataflow documentation.
no acces to the GCP
No Google console
The course "Serverless Data Processing with Dataflow: Foundations" offers a good summarize of serverless data processing, providing comprehensive content with a clear focus on the key points. Practical exercises enhance understanding, making it a valuable choice for those interested in mastering Dataflow. Highly recommended for skill enhancement.
It is what they say, it builds on the Data and ML Engineer Specialization, it was good for someone like me who already has taken quite a few qwiklabs labs and knows how to work around GCloud console, for starters I would recommend to take any other fundamental courses that cover basics of dataflow and then try this.
One of the best courses to cover fundamentals conceptual topics on Beam and some in-depth understanding of Dataflow runner and nuances on cloud. A must have training for people looking to scale on Dataflow or Apache Beam.
Lab is relatively scarce in relation to many concepts introduced in this course. More labs should be designed to help learners internalise the knowledge.
Very useful to know. I found this course very interesting.
Was mistaken about the objective of this course, its actually a very good basis, just would refine the qwiklabs challenges, its mostly an cook recipe
the google blod article from the resources page gave me more understanding than the course itself
Without deeper knowledge, this course has no benefit. You are starting with technical topics without further instructions of the goal of the course. No introduction to Vertex AI is given, instead a technical setup follows. Thats a bad introduction to get into the topic. It is not for beginners, as it is labelled.