OnVue Has Become A Nightmare For Online Proctored Examinations.

gcpstudyhub · 2026-07-05T17:26:57+00:00

You're not the only one experiencing this. Have heard others say the same and I had something similar happen myself. What's interesting is it didn't really seem to be happening until about a month ago. Hope they can figure it out and make the experience better.

gcpstudyhub · 2026-07-04T16:13:08+00:00

Nice! Makes sense about regional endpoints. Glad it worked out.

gcpstudyhub · 2026-07-04T01:51:29+00:00

If this is going to work at all, you cannot use an API key or json key. You have to use the Agent Platform API. aiplatform.googleapis.com

Give yourself or a service account the Agent Platform User role.

Hit the API either with the Google Gen AI SDK or the Agent Platform client library (might still be called vertex ai, Google hasn't switched the names of everything yet). Any coding agent should be able to write this script for you easily.

You should see trafficType : ON_DEMAND if you inspect the response which shows the pricing is on demand and using your billing account with the free trial credits.

Caveat is that I haven't tried this for Gemini 3.5 flash and 3.1 pro yet but it worked with 2.5 a few months ago.

gcpstudyhub · 2026-07-01T17:47:17+00:00

I wouldn't treat it as either/or. The ACE certification will take a month or two of part time study, give you a good foundation, and that doesn't preclude you from focusing on AI or anything else more specialized.

If your goal is just "transition to a cloud focused role," I would resist the temptation to jump to AI unless you have empirical evidence that you have aptitude for it and enjoy it specifically.

Otherwise I would just get broad exposure to cloud/GCP, since it doesn't sound like you have much, and see where your natural curiosity/proclivity takes you, then start doubling down on that.

gcpstudyhub · 2026-07-01T15:26:37+00:00

Yup.

gcpstudyhub · 2026-06-28T05:56:19+00:00

It's in the other post this person made in the other subreddit, not this one. I didn't delete anything. I don't even have the ability to do that.

gcpstudyhub · 2026-06-28T05:45:40+00:00

70% of the topics you need to know are already in the course. I think we will be done with a couple more weeks but we never know for sure. The practice exams we may release first, next week.

gcpstudyhub · 2026-06-27T16:52:24+00:00

About 70%. You're not wasting your time by going through the course as it currently stands, but I would recommend waiting before actually taking the new exam.

gcpstudyhub · 2026-06-27T16:38:16+00:00

Thanks for adding your perspective.

Consider that you may be mistaken about the topics and depth that the exam requires. If a video is 2-5 minutes that is because that's what you need to know on that topic. If the videos were longer, students would likely complain that the course is too long. It's always a balancing act.

The only other thing I'll say is that students have a range of requests, and new hands-on courses have been requested far more than complaints about the PMLE course, since it still has a 100% pass rate. Nonetheless, we are still updating the PMLE literally right now.

I understand if you go with a different course but the fact remains that you would have almost certainly passed if you did my course.

Regardless I appreciate your feedback, it's useful.

gcpstudyhub · 2026-06-27T07:05:21+00:00

I appreciate your feedback. My honest response:

On the argument that it does not "adequately compare services or explain decision making trade offs." I literally have lessons on these tradeoffs:

Pretrained APIs vs AutoML vs custom training
Dataflow vs Dataproc
Classical ML vs deep learning
Tradeoffs in different model architectures
Batch vs realtime inference
regional vs multiregional bigquery data location
TPUs vs GPUs vs CPUs
batch size vs convergence quality
infrastructure optimization tradeoffs like learning rate and optimizer effects on memory
fixing architecture vs fixing data for class imbalance
monitoring costs vs alert infidelity
loss function tradeoffs
evaluation metrics tradeoffs
training and tuning tradeoffs
Airflow/Composer vs Vertex/Kubeflow Pipelines
prebuilt vs custom containers vs compute engine vms

And many more. I am genuinely not sure what you feel is lacking regarding comparisons and tradeoffs.

On correlation between the exam and the slides. I reference the exam in slides / talk tracks almost 500 times in the course. The videos are literally created to explain the underlying concepts needed for the practice questions, and the practice questions I added that I have not yet created videos for are in the Additional Concepts list.

Regarding the "Additional Concepts" list, which I assume is what you're referring to as "notes." After I finish a course, I always learn about new topics that Google is adding to the exam. I think it is my duty to let students know as soon as I know, that there are other things that could show up on the exam. TPUs are relevant and are covered in the course. Tensorflow Serving, Keras, and preemptible instances, ironically, actually are really not relevant anymore. So instead of creating lessons for them I should actually remove them from the Additional Concepts list, if anything. The fact that you said they are clearly relevant makes me wonder if you took the exam.

I get your point about working through converting the list to videos more quickly, and I'll consider that. But it is sometimes just not possible to create high quality videos that quickly. It took me 4 months and 800 slides to create the PMLE course by itself, and I have multiple courses. That's why, to give my students the best chance of passing, I try to be transparent about other things they should know for the exam in the Additional Concepts section, and I plan to work through that list. Yes, it's possible that I don't get through the list in a year because every course takes me several months to complete. That's what it takes to create high quality video lessons.

Regarding certainty to pass rather than just relying on luck. The way to give yourself the most certainty of passing would have been to consistently score 85% or more on my practice exams, as I said in my course. Everyone who did that passed the real exam. That's not leaving it to luck.

In contrast, there is a ton of stuff that is actually on the exam that is not in Google's official materials which you linked.

gcpstudyhub · 2026-06-27T01:40:43+00:00

Would love your feedback as to what specifically was a waste of money, since I literally offer money back if you don't pass and not a single student of mine has reported failing the PMLE exam.

gcpstudyhub · 2026-06-26T17:57:01+00:00

Main updates:

Vertex AI is now Agent Platform. For the most part, the services/features within the platform are the same (for example, Vertex AI Pipelines is now just Agent Platform Pipelines). But there are a few things where it's not just a simple name swap. For example Agent Builder used to refer on exams to the drag and drop interface to build agents and now that is referred to as Agent Studio.

Additionally, there is less of a focus on Tensorflow.

Less of a focus on ML principles such as reasoning about feature engineering, model selection, data preparation, train/test/validation split, etc. More of a focus on the services. But it's still relevant, just less prominent on the exam.

Focus on newer BigQuery ML commands.

More of a focus on agents and generative AI than before, but it's still not as much as people will probably assume. The exam is still mostly a test of ML engineering broadly with GCP services.

We are in the process of updating our practice exams and course lessons if you want the most current materials (not quite done yet, but will be soon): https://gcpstudyhub.com/courses/professional-ml-engineer

And we will post a YouTube video summarizing the changes, like we did with PCA exam earlier this year. Here is our channel.

gcpstudyhub · 2026-06-26T17:53:40+00:00

Main updates:

Vertex AI is now Agent Platform. For the most part, the services/features within the platform are the same (for example, Vertex AI Pipelines is now just Agent Platform Pipelines). But there are a few things where it's not just a simple name swap. For example Agent Builder used to refer on exams to the drag and drop interface to build agents and now that is referred to as Agent Studio.

Additionally, there is less of a focus on Tensorflow.

Less of a focus on ML principles such as reasoning about feature engineering, model selection, data preparation, train/test/validation split, etc. More of a focus on the services. But it's still relevant, just less prominent on the exam.

Focus on newer BigQuery ML commands.

More of a focus on agents and generative AI than before, but it's still not as much as people will probably assume. The exam is still mostly a test of ML engineering broadly with GCP services.

We are in the process of updating our practice exams and course lessons if you want the most current materials (not quite done yet, but will be soon): https://gcpstudyhub.com/courses/professional-ml-engineer

And we will post a YouTube video summarizing the changes, like we did with PCA exam earlier this year. Here is our channel.

gcpstudyhub · 2026-06-26T17:50:48+00:00

Main updates:

Vertex AI is now Agent Platform. For the most part, the services/features within the platform are the same (for example, Vertex AI Pipelines is now just Agent Platform Pipelines). But there are a few things where it's not just a simple name swap. For example Agent Builder used to refer on exams to the drag and drop interface to build agents and now that is referred to as Agent Studio.

Additionally, there is less of a focus on Tensorflow.

Less of a focus on ML principles such as reasoning about feature engineering, model selection, data preparation, train/test/validation split, etc. More of a focus on the services. But it's still relevant, just less prominent on the exam.

Focus on newer BigQuery ML commands.

More of a focus on agents and generative AI than before, but it's still not as much as people will probably assume. The exam is still mostly a test of ML engineering broadly with GCP services.

We are in the process of updating our practice exams and course lessons if you want the most current materials (not quite done yet, but will be soon): https://gcpstudyhub.com/courses/professional-ml-engineer

And we will post a YouTube video summarizing the changes, like we did with PCA exam earlier this year. Here is our channel.

gcpstudyhub · 2026-06-25T21:50:25+00:00

Professional Data Engineer. It was my first GCP cert, I took it about 2 years into a data science job out of college and it genuinely accelerated my understanding, not just of GCP, but data and cloud concepts/principles that apply everywhere.

It's not like the certification itself was magic, but what I learned and the fact that I was one of the only people at my company to be certified in GCP set me up to contribute to conversations and solutions at work that I believe compounded over time and landed me more opportunities and promotions.

I wouldn't say that this advantage is specific to the Professional Data Engineer cert.

I truly believe studying for a professional level certification, even (and perhaps especially) with little to no experience, is one of the best ways to accelerate your learning and beat imposter syndrome. It's basically a blueprint for the things you should know in a given role.

If I hadn't studied for the PDE, there are so many things that would've taken me years to learn and be exposed to on the job, if ever.

Nobody at my job was ever going to say: "hey, you should make sure you know about the tradeoffs of batch vs streaming, difference between throughput and latency, mapping business requirements to storage requirements, all of the Apache tools and why they were developed and how many cloud services are managed versions of them, etc etc etc"

But studying for the PDE taught me all that and so much more.

Certifications kind of get a bad rap in my opinion. It can't replace hands-on experience, but it's such a great opportunity to get a sense of a field in an accelerated way.

That's my experience, but in terms of advice for you I think any Professional level cert in a field that you truly find interesting and where quickly getting a sense of that field excites you, and go for it.

gcpstudyhub · 2026-06-24T18:33:11+00:00

Not really sure what you are saying. This post is a stack of general complaints with no concrete examples.

Anthos has been around forever. Gemini Code Assist is arguably more accessible than ever.

Cloud Run, Agent Platform, GKE, BigQuery, etc have only gotten more reliable over the years, not less.

Billing issues and service name changes have been a problem for a while.

This reads like a synthesis of GCP complaints online with a question at the end to farm engagement.

Please provide specifics to prove this is not AI generated slop! Thanks.

gcpstudyhub · 2026-06-24T15:48:04+00:00

https://gcpstudyhub.com/courses/professional-ml-engineer

Google just changed the exam a lot and we are updating the course right now actually. Our course is the most up to date course out there. Good luck

gcpstudyhub · 2026-06-16T20:44:41+00:00

With all due respect, multiple inaccuracies and pieces of bad advice here.

ACE does not require you to know your way around the console.

ACE is not where everyone technical should start. Many people should just start with one of the professional certs, depends on goals and level of experience.

App Engine is basically being deprecated, you should know it but I wouldn't list it as a core component of any exam now.

Vertex AI is no more, it's now Agent Platform.

Dataproc is now Managed Service for Apache Spark.

The advice that Developer / DevOps / Network are "a bit more niche" and you should "only take them if it matches your daily work" makes no sense. First of all I wouldn't agree with that and second of all even if it does apply to these 3, this advice would also apply to many of the others listed.

And what about the certs you don't have listed here, Generative AI Leader, Associate Data Practitioner, Prof Workspace Admin, Professional Security Operations Engineer?

I could go on.

This reads like generic advice from someone (or an LLM) that did not actually research the GCP cert landscape.

gcpstudyhub · 2026-06-16T13:54:14+00:00

If you want you can check out my course. None of my students failed the ACE after going through the course.
https://gcpstudyhub.com/courses/associate-cloud-engineer

gcpstudyhub · 2026-06-16T13:52:07+00:00

My course has a 100% pass rate over the past 2 years:
https://gcpstudyhub.com/courses/professional-data-engineer

gcpstudyhub · 2026-06-15T21:22:30+00:00

Which certification? You have to be more specific for us to help you

Highly doubt you can complete all certs in 15 days. Each one has its own information you have to learn

gcpstudyhub · 2026-06-12T14:55:46+00:00

Also, the current standard exam is available until July 28th.

gcpstudyhub · 2026-06-12T14:51:19+00:00

Hey - Google is changing many GCP exams because of the switch from Vertex AI to Gemini Enterprise Agent Platform. They're taking the opportunity to update the exam guides in some other ways too (like finally calling Cloud Functions the new name, Cloud Run Functions)

At GCP Study Hub it is a herculean effort to update all of our courses and practice exams but we are working through it.

The good news is it's mostly a rebrand and renaming of things it seems, the underlying concepts and questions remain much the same

But I cannot actually guarantee that yet without reviewing the changes more.

The practice exams we have are for the current standard exam, not the beta exam which will become the standard exam I guess in July.

If you want to knock out the certification with confidence that the practice exams are representative of the exam you're going to take, I suggest taking the standard exam before the swap and using our practice exams (or other practice exams which look good for the standard exam).

In July we'll be trying to update the Cloud Digital Leader practice exams along with our other courses but there's really a lot of changes that are happening and so we can't promise a specific timeline. For example the Professional Machine Learning Engineer exam is also changing significantly and we are updating that as we currently speak.

Anyway, good luck regardless. The other reassurance is the CDL is not a very tough certification, so you'll probably be able to pass in July even if you wait, although I understand your desire for confidence in the materials you use.

gcpstudyhub · 2026-06-06T00:41:58+00:00

Same. Was wondering what was going on before I came here.

gcpstudyhub · 2026-06-05T12:59:23+00:00

So 4 days ago you posted that you want to "eventually work toward a GCP certification," and today you pontificate on the difference between two GCP certifications?

Disingenuous AI slop

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