Apache Beam | Google Data Flow (Python) | Hands on course (Udemy.com)

Great course! The instructor explains Apache Beam concepts—batch and stream processing, transformations, windowing, late events, Beam SQL, and Google Cloud Dataflow—very clearly with Good Python examples. Her communication is excellent, and the content is short, focused, and easy to understand. Perfect for getting a quick, practical foundation.

This class has been very beneficial to understanding Apache Beam and is a great companion piece to understanding GCP Dataflow. Very detailed breakdown of the key methods in Python and worth review and doing the hands on lessons.

This is a good course for exposure to Apache Beam, and all of the functionality indicated in the description works fine. That said, especially for technology that is fairly fast-moving, some of the content is a bit stale, and it's hard to know what you're missing out on without an updated. For example, there were numerous references to features that weren't available for Python at the time of recording, but which probably are available 4+ years later. Another example is the last lectures that dealt with Beam SQL, which is probably still available but at the very least doesn't exist at the same location in GCP anymore. So I did get what I wanted out of it, but know I'm missing out on some newer functionality/features. Also always appreciate challenges/assignments, which weren't included in this iteration, but the instructor does make it easy to code along most of the time!

It lacks content, it would be good if you did an example of ETL (Extract, Transform, Load) from an API, extracting data from a file is very basic, hopefully you can update the course with that example.

There was some useful content covered in these lectures, but I feel that this content was covered in as much depth as I would have liked it. Also, sample code has really poor coding practices which are worth cleaning up.

As there are few resources using the Python SDK, this course is a good introduction to Apache Beam using PYthon. I was expecting more real examples regarding different scenarios using windowing. Besides that, I recommend this course.

Comprehensive coverage of Apache Beam. Good set of examples for both batch and streaming use cases. It would be great if you could add some more material for DataFlow, like, InteractiveRunner and how to create custom templates etc .. Overall a great course to quickly ramp up on Apache Beam using the Python SDK. Well Done !

The course is good, but it should also include how to deploy Apache Beam on GCP Cloud Dataflow, or some other runners. Also, please add a course with JAVA SDK also, so that folks writing code in Beam Java can understand. Adding Beam SQL would help too. Also- please provide a session on how to deploy Beam code to Dataflow and Spark- so that folks can know the difference. Windowing concept is nicely explained- but can be refined if we can use eventtimestamps as well. Thank you for the amazing course!

You will go into heaven!!! I was looking for python related streaming and batch processing on Apache Beam and this course was designed exactly for that. Thanks a ton! Waiting for the announcement for rest of the topics on this course. Thanks again!

I liked this introductory course very much. It basically displayed the structure of the Google Pub/Sub Pipeline using Apache Beam. May I know when are you expected to make the detailed Apache Beam (Python) for Google Pub/Sub, Dataflow course available? Thank you!