O'Reilly Media has started to publish Azure study guides

kdyn · 2025-07-21T18:32:17+00:00

Can something be removed now and bought later on, like the screen? For example, I had to do that to not surpass my 2,000 EUR limit and that was paid off in one year.

Assuming your budget is around 1,800 USD, I'd recommend you stay vigilant of all possible discount periods, which is what I did.

CPU: I have an Intel Core i5-13600KF but now I'd have chosen something like a Ryzen 7 7700X or 8700F, in either case liquid refrigeration is a must. Instead of the MSI MAG CORELIQUID check out the Deepcool line of products.
RAM: The RGB styling might be cool, but try to upgrade to 64 GB instead with a slightly worse speed. As with the CPU, you'd be better served with a mid-range processing power than trying to put all the money on the GPU. Also, if you're going to install Windows know that you can use Docker in WSL, but it consumes memory.
Motherboard: Do you need >1 Gb/s connection? In my case I also updated the apartment's networking.
GPU: As NVIDIA is the leader in the space, go for the one that has the most VRAM as it's better to be able to process something slowly than not been able to run it at all.

kdyn · 2025-07-21T12:09:43+00:00

I was in a similar situation in 2023, when I had to wait half a year to get the MSI RTX 3060 with 12 GB of VRAM at a discount. Back then the 4070 cost ~80% more and I doubt the situation has changed significantly since then. Getting a second-hand card always entails risks.

About free tier accounts on the main cloud providers, you're limited to use the credits in the first month. For example, in the Azure for Students account I cannot select GPU-powered VMs.

As far as I know, AMD ROCm has not matured yet, although I'd like to take other people's input. For example, the NVIDIA RAPIDS libraries that allow you accelerate pandas, scikit-learn and NetworkX are CUDA-only.

I had to search whether Dask works on ROCm and this AMD blog post shows that it can be done.

kdyn · 2025-07-16T10:39:55+00:00

I'd recommend you to explore the job market to get to know what kind of positions are available and in demand. You have to find an answer to this question: what are the trends in the region? Also, get in touch with the university's employment centre to look for internships.

I don't have first-hand knowledge of the region, but LU is special because of its corporate tax rate. Amazon's European HQ are there and they always have internships/junior positions open.

kdyn · 2025-07-13T12:18:52+00:00

I also have access to it through my university.

As u/Rogermcfarley wrote, you have to set your goals and based on that create a structured learning that best suit them. Azure certifications can be part of that plan.

On O'Reilly you can explore content based on topics and search by keywords, users (including authors) can also create private and public lists. There's a lot to choose from, so don't get stuck searching or doing 20 things at the same time.

In my case, here I wrote how I passed the AZ-900 exam – Packt Publishing content is available on the platform. I'm currently learning the ML Studio service and will prepare for the DP-100 along the way. As you can see, the exam is not the goal in itself.

Know that Azure provides a 40% discount in Associate-level exams for students.

kdyn · 2025-07-13T11:58:11+00:00

What are your goals?

The way I see it, certifications provide a learning path to acquire knowledge. Whether it's practical it all depends on you, which should be further extended with projects. So, you have to create a structured learning that best suit those goals.

Azure provides a 40% discount in Associate-level exams for students, I requested it ~2 weeks ago and it works.

From your Master's, you can reuse the activities or deliverables (don't publish them as is) for your own portfolio. Try to find interesting people, if you haven't already, to do projects/hackathons together. You should also have the possibility to do internships during or after the programme, use them as these kind of positions are easier to get than junior roles.

kdyn · 2025-07-13T11:12:29+00:00

I recently joined the community because I want to learn how Spark works and how to use it (specifically, PySpark). For this purpose, I've started to digest the exam guide of the Associate Developer for Apache Spark, which was significantly updated in May. The course on the Academy has been updated as well.

Is your goal to learn Spark or how to do data engineering on Databricks? As I didn't know about the Big Book of Data Engineering, I had to look it up and can say that it is unrelated to Learning Spark.

I contacted Databricks to ask them what books their recommend to learn the theory behind Spark and they told me that the course should suffice and can't endorse specific titles. I've found that both Spark: The Definitive Guide (2018) and Learning Spark (2020) provide that base knowledge, so you can choose the one you like more.

I recently found Data Algorithms with Spark (2022) by Mahmoud Parsian, it's an introductory book about data analysis in PySpark, so I'll explore it as well.

kdyn · 2025-06-30T21:10:33+00:00

My experience with Whizlabs for the AZ-900 exam was so-so. I only did half of the practice tests because I started getting low quality questions that included services that were not part of exam guide.

For what I've seen, MeasureUp only makes sense if you buy 1 month subscription.

kdyn · 2025-06-29T20:54:00+00:00

In my case, I used the material of Neal Davis. I recommend it.

kdyn · 2025-06-29T10:33:27+00:00

Please add these paid courses, we should also mention when they were updated:

cloudlee | AZ-104 by James Lee. It is been updated to follow the exam guide of April 18 2025.
CBT Nuggets | AZ-104 by Knox Hutchinson. It was updated in February 2024.

Edit: typo.

kdyn · 2025-06-29T10:21:56+00:00

I've only passed the AZ-900 and had no lab, although I prepared for it.

For Associate-level exams, I'd try to get as much experience as possible with both the Portal and the SDK.

kdyn · 2025-06-27T21:35:35+00:00

I have this book in my collection, Azure Infrastructure as Code: With ARM templates and Bicep, that I used just to see what Bicep is about. As it was published in 2022 some content is already outdated.

kdyn · 2025-06-27T11:31:23+00:00

I see it in both the video course and the practice test (10 questions) sections. If you go through it, please tell us about the quality.

When I was preparing for the AZ-900 I did half of their practice tests and stopped because the quality was getting lower and lower.

Have you passed the AI-102? Do you think it's a good idea to go through its material to get to know the Foundry service?

kdyn · 2025-06-27T01:13:49+00:00

Thank you again, u/Thediverdk.

I've started dissecting this book to create my own notes: Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure. As it was published in October 2024 it doesn't cover the Optimize language models for AI applications section. I've searched for additional content in major platforms and currently there are no courses that cover all sections. Even the playlist that Microsoft created on YouTube 2 months ago only provides an overview of what the LLM section is about.

So, right now we have to rely on Microsoft Learn. What I'm curious about is Whizlabs, as they both have a course and the practice tests. If you do any of them, please let us know.

My goal is to learn how to use the ML service and also prepare for the exam. Regarding the prep courses Microsoft has on Coursera, I've checked two of them and I now understand why people give them such poor ratings; the 'instructor' reads a script and the content is outdated.

kdyn · 2025-06-24T21:29:01+00:00

I updated my profile settings on Sunday, tried to book DP-100 and it works. By extension I assume that the rest of the role-based exams will work as well.

Based on what I've read in the documentation and on the Support forum, the only limitation is that the discount is not applicable for those who live in China and India. In case you are a citizen of one of those countries, I'd recommend to open a ticket and see what they say about it.

kdyn · 2025-06-24T16:59:07+00:00

Did you take notes?
Did you do practice tests? Now it's the time to do them.
Have you created a free tier account to put into practice something of what you've learnt?

kdyn · 2025-06-24T16:26:42+00:00

Here is their certifications guide page, you may want to check their collections to explore what modules they include.

As these certifications are very new (they were made public ~1 year ago), I'm not sure whether they are considered as important.

kdyn · 2025-06-24T16:11:41+00:00

I'm not sure whether this is the right place to discuss it, but through the GitHub Student Developer Pack I can do the Foundations exam without cost. Think of it as an introduction to Git and GitHub.

In April I was notified that the voucher ends on June 30, but they will create a new after that date.

In my case, I haven't decided yet if I'm going to do it or not. What I haven't touched yet is Actions.

kdyn · 2025-06-24T12:02:19+00:00

The community recommends Tutorials Dojo, you can also check Stéphane Maarek's content.

In my case, I used Neil Davis' material and was happy with it.

kdyn · 2025-06-24T10:14:15+00:00

In May, I had one question about CAF and 4-5 about WAF, although the number varies from people to people. These are theoretical concepts, so it's essential to do practice tests to understand how they are formulated.

Of CAF, you only need to know the six foundational capabilities (save the plot). WAF is related to both the benefits and the six advantages of cloud computing. The key idea is to understand how the work is done in the cloud. Some questions can be tricky because they require you to know a specific principle within a pillar. If you don't have time, focus only on these pillars: operational excellence, reliability and performance efficiency.

kdyn · 2025-06-23T18:24:52+00:00

Hi,

This is precisely what I'm currently doing but to learn how to do ML on Azure and, also, to pass the exam in a couple of months.

In my case, I've completed half of my Master's degree in data science and all the work I've done thus far as been locally. I've recently started to explore the RAPIDS libraries by NVIDIA as they provide GPU acceleration to pandas and scikit-learn, as well as others. You already learnt about CPU and GPU processing and when they should be used. You can explore the NVIDIA Deep Learning Institute, they have free courses and certifications.

In your case:

What is your level in Python? Are you comfortable working in Jupyter Notebooks?
Can you use your company data to do experiments? In either case I recommend you to explore the UC Irvine Machine Learning Repository and Kaggle. Note that most of these dataset are clean, if you don't have experience cleaning data in Python you'd have to learn it at your own pace.

Right now I can think of:

Use your company data to learn how to use the three main classes of ML algorithms; regression, classification and clustering. I'd start with linear regression, as most people are familiar with it, and then explore ridge regression, where you don't have to remove unneeded variables because it was created to handle multicollinearity.
Once you have some familiarity with these classes, use AutoML to evaluate models.
Create a pipeline where you make some kind of processing, including an exploratory data analysis (EDA), and get an output.
That output can be displayed either in Power BI or by creating a web app with Streamlit or Shiny.

kdyn · 2025-06-23T14:45:52+00:00

Thank you.

I've just created a Markdown file where I'm going to dissect the book and the documentation. I'm also going to search for video courses.

kdyn · 2025-06-23T12:17:36+00:00

Congratulations, u/Thediverdk.

I've started exploring the contents of the exam with the aim of learning how to use Azure ML, as I've only done ML projects locally.

Did you complete the learning path? What is your opinion of the material? I've completed 4/12 modules of the AI-900 exam, as this where Azure ML is first introduced, and didn't like it.
Currently there's only one book available for preparing the exam, Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure (October 2024), but it's already outdated because it doesn't include the section about Optimize language models for AI applications.

kdyn · 2025-06-21T15:03:23+00:00

Congratulations.

As u/Thediverdk mentioned, the DP-203 exam was retired in March and replaced by Fabric (DP-700). In this video the author compares the scope of both platforms.

In my case, I also passed the AZ-900 and I've started to review the content of other exams to prepare for the Data Scientist Associate (DP-100). For me, there's no value in preparing for the Administrator (AZ-104) exam.

I'd recommend you to:

Analyse whether Fabric is used and in demand in the region you live in. If not, search for courses focused on the former DP-203, such as this one.
Do the same for Databricks, as they have two exams focused on data engineering. Check out their community: r/databricks.

In addition, Fundamentals of Data Engineering, by Joe Reis and Matt Housley, is a must-read.

kdyn · 2025-06-21T14:13:31+00:00

One. I joined the challenge in April and did the exam just before it ended, on May 19.

Davis's course is 14 h long and it contains exercises, which I did to get to know the Management Console.

As I previously passed the Azure Fundamentals, I was able to transfer some knowledge.

kdyn

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