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Quite a few reached out who wanted to know about the GCP Authorized Trainer program. The information on the net is very, very thin. I think this will be very useful for them.

https://medium.com/@sathishvj/google-cloud-platform-authorized-trainer-1b202f3eef61

https://github.com/ml874/Data-Engineering-on-GCP-Cheatsheet/blob/master/data_engineering_on_GCP.pdf

Hi David,
Not sure in you want to add this however here are my study notes. I need to do the exam again at the end of the year so it will be updated then.

https://github.com/grantcarthew/notes-google-cloud-architect

Regards.

I've recently taken and passed both the Cloud Architect and Data Engineer exams.

I've shared my preparation process, as well as study guides (TO-DO list style) for both exams in this post: https://medium.com/@ivam.santos/how-to-pass-both-the-cloud-architect-and-data-engineer-gcp-certifications-bb6a0812a1b1

Feel free to add it as a reference in your docs if you feel it's a good fit.

Cloud Guru free course for ACE on Udemy: https://www.udemy.com/google-certified-associate-cloud-engineer/?couponCode=GCPFREELY

Mete Atamel's notes on PCA:
https://medium.com/google-cloud/professional-cloud-architect-certification-6a6dfa5c6ff5

I'll try to keep this updated, hopefully with others also letting me know when there are free codes.

https://medium.com/@sathishvj/qwiklabs-free-codes-gcp-and-aws-e40f3855ffdb

For now only coursera courses seem to be there. But I guess others like linux academy could add theirs.

https://www.class-central.com/institution/googlecloud

I don't know if this is a popular site/listing though.

Exam preparation
While hands-on experience is invaluable, sometimes you miss on a bigger picture of the available infrastructure when you find yourself working only with a subset of available GCP network technologies. Here is what I’ve used:

David das Neves: Awesome GCP Certifications
Coursera: Data Engineering on Google Cloud Platform Specialization - not a quick course, but covers material well, gives an opportunity to practice what you’ve learned in QuickLabs.
LinuxAcademy: Google Cloud Certified Professional Data Engineer
Qwiklabs: Data Engineering
YouTube: Introduction to Google Cloud Machine Learning (Google Cloud Next ‘17)
YouTube: Auto-awesome: advanced data science on Google Cloud Platform (Google Cloud Next ‘17)
YouTube: Lifecycle of a machine learning model (Google Cloud Next ‘17)
An actual exam
Two hours, 50 questions. It took me 1 hour for the first pass; I had 21 out of 50 questions marked for review (shows the amount of self-doubt this exam will inflict upon you). I’ve finished the entire exam in 1 hour 15 minutes and was presented with much doubted “pass”.

Preparation suggestions
I do not intend to share any of the actual questions as this is against certification’s mission. Topics I’ve covered before are the ones that I’ve found harder or less prepared for after taking all of the training above.

Key topics: BigQuery, BigTable, Dataflow, PubSub

BigQuery
Streaming data into BigQuery - know it well.
High-rate streaming
Serving large datasets to BI dashboard (focus on data freshness and cost efficiently)
Benefits of partitions
From the point of view of BigQuery administrator ensure that you know best practices on how to allow various teams access team specific datasets without cross access.
Methods to increase the number of concurrent slots
How to verify that ETL migrated to BigQuery produced equal results
Point in time snapshots BigQuery
Integration with BigQuery ML
UDFs
Understand the pros and cons of denormalised data in the context of BigQuery
BigTable
Understand architecture and key reasons for high performance well
Know Key Visualiser
Know when to scale BigTable
Know performant key/schema design
Scaling up BigTable
If you need to double your reads for a prolonged period, what can you do to guarantee the same read latency?
Dev to Prod cluster promotion
HDD to SSD data migration
Dataflow
Understand Apache Beam building blocks - Pipeline, PCollection, PTransform, ParDO
Know Side Inputs
Exactly once processing of PubSub messages
Handling invalid inputs
PubSub
Migrate from Kafka to PubSub
Know potential reasons for PubSub ingesting applications being busier than initially planned
What PubSub metrics are available in Stackdriver and how to debug producers/consumers
Ordering messages
Dealing with duplicate messages
Data migrations
Know when to use Data Transfer Appliance. Hint - slow network, huge dataset, no in-between refreshes.
When to use Transfer Service and what are its limitations.
Know the cost of storage and availability for various products: BigQuery, BigTable, Cloud SQL, GCS to be able to find the cheapest product for a set of availability/durability criteria.
How Dedicated Interconnect impacts your data transfer decisions?
How to continuously sync data between on-prem and GCP
Dataproc
Cloud Storage connector
Preemptible workers
Scaling clusters
ML
Know best practices for training ML models (training, test, overfitting detection)
Speeding up TensorFlow applications
Know Cloud Data Loss Prevention API
Know Cloud Natural Language API
Know Cloud Vision API
IAM
How to allow cross team data access to BigQuery and GCS in a large organisation
Misc
Know how to backup, migrate Datastore
Know Cloud Composer well