I am a new one to the AI field, and this year I decided that this is a time to sharpen my skills. One of the pillars of AI is infrastructure, which is somewhat different from the traditional one used for running typical applications and virtual machines.
I started with the NVIDIA technologies and solutions as the leader in a modern AI infrastructure. NVIDIA provides a lot of training materials, documentation, and certifications on its technologies. It looks like a good way to start, because I believe that the best way to learn is by pursuing the certification.
Recently I completed the NVIDIA-Certified Associate: AI Infrastructure and Operations certification, and in this post, I want to share the materials I used to successfully pass the exam.
NVIDIA-Certified Associate – AI Infrastructure and Operations is an entry-level certification, covering concepts of AI computing related to infrastructure and operations.
As mentioned in the study guide, “This exam is for IT professionals who are new to AI operations and infrastructure but who are required to understand and describe the different components and aspects of adopting AI in data center environments and on prem environments.”
Briefly about the exam:
The exam costs $125; it consists of 50 questions, and you will have 60 minutes.
The exam is online and proctored remotely on the https://www.certiverse.com/ platform. This is one of the best and simplest platforms I’ve used so far. Fast booking and fast check-in, including the ID and room scans.
As always, you need a computer with a camera and microphone, a stable internet connection, and no one in the room.
The exam covers current topics:
Accelerated computing use cases;
AI, machine learning, and deep learning;
GPU architecture;
NVIDIA’s software suite;
Infrastructure and operation considerations for adopting NVIDIA solutions.
And divided into three sections:
Essential AI knowledge;
AI Infrastructure;
AI Operations.
Do not be afraid. All topics requiring the basic knowledge.
Let’s move to the exam and preparation:
Before we begin with an AI infrastructure, we definitely should know what AI is, what it looks like, and so on.
You may see a post on my blog where I posted links for two completely free Red Hat courses describing AI basics.
As a minimum, I highly recommend completing the Red Hat AI Foundations – Executive course, and if you want to dig a bit deeper, Technologist.
Both courses will give you essential basic knowledge on AI, and you can start to learn what infrastructure looks like.
When we learn the basic AI theory, it’s time to open the NVIDIA-Certified Associate: AI Infrastructure and Operations Exam Study Guide.
This guide outlines all topics you can face during the exam; each section contains recommended reading and training course modules covering this part of the exam.
Training:
Although recommended training is marked as an optional option, this is where I highly advise you to start.
The recommended training course is AI Infrastructure and Operations Fundamentals. It costs $50 on NVIDIA’s site and covers most, if not all, exam topics.
As an option, you can buy a bundle – training + certification, which will cost you $150.
As an alternative, you can check out the AI Infrastructure and Operations Fundamentals course on Coursera. NVIDIA officially offers this course, but I’m uncertain if it’s the same as the one accessible on the NVIDIA portal. The big bonus – you can enroll in it for free.
In my case, I started with the Coursera training, and the amount of material in this course was sufficient to successfully pass the exam.
The course provides necessary material, basic theory, features, use cases, and terminology. It includes small tests after each unit and a larger test at the end of the course.
What I really don’t like is that this course is a series of videos, and you can’t copy-paste something you want to repeat later or not to forget. And my advice here is to make screenshots. If you think that something could be important, make a screenshot. By the end of the course, I had a big document with screenshots, and I used it before the exam to repeat everything in a very fast manner.
One more course to check out is free InfiniBand Essentials. Although IB is not the biggest part of this exam, it is the key component of a large AI infrastructure, and we definitely should know about it.
Reading:
As with any associate exam, this exam covers many different topics, and it’s hard to recommend one or two documents to read.
At the end of the exam description page on the NVIDIA portal, you can find additional materials recommended to review; it won’t take more than a few hours, so I recommend checking them out.
Practice:
There are no practice tests, but the test at the end of the training course looks like something you can see during the exam.
In addition, we are learning about AI, right? You may choose any chatbot you prefer, such as ChatGPT, Grok, or DeepSeek, to ask you questions about NVIDIA AI infrastructure and technologies and to give you several options for answers. You may ask a bot to explain the answer and learn increasingly in a simple manner. However, don’t forget that these bots may be a bit outdated and might not be aware of the current technologies, speeds, and models. For example, they may not know about B200 GPUs.
It will not be like real exam questions, but I’m 100% sure you will get yourself more familiar with the terminology, NVIDIA solutions, and use cases.
Summary:
In short, to succeed in this exam, I recommend completing the suggested training, as it likely accounts for 90% of your success. After that, read the recommended additional materials, and practice with a chatbot.
I wish you all good luck and hope this article can help you to prepare.
