Let me guess. You probably made a New Year's resolution to learn AI. You probably started an AI course and you abandoned it in one chapter.
And I wouldn't blame you at all. Now, unless you live under a rock, you probably know how hyped AI is right now. So, naturally, there are hundreds of options for AI courses out there right now.
Everyone online is recommending something different. And it's almost impossible to tell which credentials actually matter versus which ones just look good on paper. So today I am ranking seven AI certifications from the ones that are genuinely career changing, the ones that are solid but maybe situational and the ones that I would skip entirely so that you don't waste another 3 months on something that's not going to make a difference.
And this would be ranked using this scale where a tier is exceptional ROI, strong market demand. It is a must-have for [music] that career path that you're choosing. B tier means it's solid and valuable, but it might be situational based on your tech stack or requires significant investment relative to where you are in your career.
Ctier means it has some value in some specific context, but it isn't going to really make [music] a big difference the way that you think it will. And D tier means I wouldn't recommend it at all and you got to move on. So, if you have been waiting for someone to just cut through the noise and tell you exactly where to start, let's get into it and start with the certification that so many people have but is so overrated, which is the Chachubt and OpenAI courses that exist on learning platforms like UDI and LinkedIn Learning.
So these are certifications where an independent instructor builds a course around chatbt or other open EI tools you work through it and you get a certificate at the end which sounds pretty straightforward right but if you started a course like this and then you quit it halfway through I don't blame you because this certificate is not impressing anyone in the way that you think it will. Now I do want to call out that OpenAI is building their own official certifications and that is completely different from this category that I'm mentioning here. The reason that those are [music] not on this list is that they're still in early pilot stages and they're not widely available yet, but they are coming and they are worth paying attention to.
So, I did a full breakdown of what OpenAI is building in this video. But in terms of these like third-party track certificates, I am giving them a C-tier ranking. So many of them have shown up so fast and in so many different platforms that hiring managers at competitive companies have basically stopped taking them seriously.
When a recruiter sees something like chatbt certified from some random UDMI course, it just doesn't carry the same weight as a certification that might have come directly from companies like AWS, Google or IBM. Now, I'm not saying that these certificates are completely worthless. Here's where they do make sense though.
If you are in a non-technical role like marketing, operations, or HR, and you just want to show your team that you are actively using AI in your day-to-day work, a core certificate is going to be better than nothing at all. It at least shows that you're paying attention, which is bragging points in my books. But if you are going after a technical AI role and these are your only credentials, well, that's a problem because the time that you spent collecting five of these could have gone towards building something that actually solves real problems that you can show off to employers.
Certification number two is the AWS certified machine learning specialty. According to Skilloft's IT skills and salary survey, AWS certified machine learning specialty holders report an average salary of 171,725. I know that's super exact, but that is the highest average salary that is tied to any WS certification out there.
And the exam cost only $300. That ROI is pretty insane. AWS built this for people who design, implement, deploy, and maintain machine learning solutions.
It covers concepts like data engineering, modeling, ML operations, endtoend. So, this isn't just one of those like awareness certifications. It is a deep technical credential that proves that you can actually build and run production ML systems at scale.
So because of all those reasons, I am giving this one an A tier ranking. AWS [music] has the largest cloud market share globally, which means that the majority of enterprise ML workloads are running on the AWS infrastructure. Now, one thing I do want to bring up is that AWS recommends at least a year of hands-on experience with SageMaker and their ML services before you even attempt this exam.
So this is not one that you want to start at. But if you are already working in data science or ML engineering on AWS, then there you go. This is your next move.
You are welcome. Certification number three is the Microsoft Azure AI Fundamentals AI 900. I have seen this one get recommended constantly for beginners and I understand why.
It's pretty affordable at $165. You don't need any coding experience and it's from Microsoft. So [music] on paper it looks like the perfect place to start.
But I'm giving this a C-tier ranking. That's suspicious. So AI 900 teaches you AI concepts and how Azure services work at a pretty surface level.
And in 2026, that's just not enough to impress anyone anymore. Hir managers aren't looking for people who understand AI in theory. They want people who can actually build, deploy, or manage AI systems.
And AI 900 just doesn't show that for you. Where it does make sense though is as a stepping stone. Microsoft actually positions it that way themselves.
This one is designed to lead into their more advanced AI 102 certification. So if you are brand new to Azure and you need a structured foundation before tackling something more serious, it can serve that purpose. But if you are putting AI 900 on your LinkedIn as like your main AI credential and expecting companies to be impressed, I hate to break it to you, but that's not going to set you apart.
Certification number four is the Google Professional ML Engineer. So Google built this one as their flagship credential for serious ML practitioners out there. It is focused on designing, building, and running ML models on Google Cloud using tools like Vert.
ex AI and BigQuery. Now according to data quest employers are specifically looking for this certification when they are hiring for computer vision NLP or production ML roles. So for those reasons I am giving this one an A tier.
Then there's also research from new camp which shows that holders of this certification see about a 25% salary bump compared to peers without it. And because Google really is an AI first company. You and I both know this.
This certification really reflects that. You're not just learning to use AI tools. you are learning to build and ship production grade ML systems the way that Google's own engineers do.
Google recommends at least 3 years of industry experience before taking this one including a year on Google Cloud. So like the AWS ML specialty, this is for people who are already working in ML who are ready to specialize and earn more. Last thing I want to mention about this one is that this certification tends to show up at more of those cuttingedge AI companies and research forward organizations while the AWS ML specialty is more common in traditional enterprise environments.
So you want to think about where you actually want to work before deciding between those two. And now number five is the IBM AI engineering professional certificate on Corsera. If you're trying to break into AI from a nonML background, this is one of the first ones that I would recommend to you.
IBM updated this program back in March of 2025 with new generative AI content. So you are learning what is actually relevant right now rather than stuff that was hot like 3 years ago because trust me, there have been a lot of changes in this space over the past 3 years. I am giving this one a Btier ranking.
The [music] hands-on projects are the real value here. So, you can walk away with actual work to show on your LinkedIn and in interviews, which honestly [music] matters just as much as having the credential itself. It costs around $49 a month on Corsera and it takes most people 6 to9 months to complete it.
So, [music] you can do the math. But the reason it is a B tier and not an A tier is because IBM's name just doesn't carry the same immediate recognition that hiring managers would have for companies like AWS or Google Cloud, if I'm being completely honest. But, you [music] want to think of this as like your runway.
It builds the technical foundation and the portfolio that you need to go after those A tier certifications later. So for anyone earlier in their AI journey, this is one of the most practical places to start. Certification number six is the CompTIA AI Plus.
That is a mouthful. CompTIA launched this one in 2025 and it got a lot of attention for it because CompTIA is definitely a respected name in the credentiing space. They are behind security plus which I have talked about in previous videos about a gatekeeper credential in specific industries.
So when they put out this AI certification, people were paying attention, but I am giving this one a C-tier ranking as well. The problem here is that CompTIA AI plus is vendor neutral. And that sounds like it could be a good thing, but it is actually a pretty big limitation in the AI market right now because when a hiring manager at a company running on AWS sees your resume, they want to know that you can work with their specific tools like SageMaker and Bedrock.
CompTIA AI plus tells them that you understand AI concepts in general, like in a very abstract sense. But that is a pretty different signal from having an AWS specific one. The AI job market in 2026 is platform driven.
Companies just aren't hiring people who get AI. They are hiring people who can actually implement it on the specific cloud infrastructure that they are already using. So a vendor neutral credential just doesn't prove that.
Now that being said, if you are in a non-technical role like a project manager, business analyst or someone in like a leadership role who needs to speak intelligently about AI without having to go too deep on a specific platform, then this one would make more sense. But for anyone going after a technical AI role, your time is better spent on credentials from platforms like AWS, Google or Azure. And so speaking of Azure certification number seven is the Microsoft Azure AI engineer associate AI 102 which I had mentioned earlier.
Now this is honestly the certification that Microsoft should have been telling people to get instead of AI 900 which I mentioned earlier where AI 900 teaches you concepts. AI 102 actually tests whether you can design and build AI solutions using Azure's tools. So NLP, computer vision, conversational AI, all of it.
I am giving this one a B tier ranking. And here's why. Azure runs the backbone of a lot of those large enterprise companies.
So if your target employers are these big corporations rather than AI native startups, then AI 102 is a strong one for you to consider. The exam is around $165 and Microsoft recommends 3 to 6 [music] months of prep. So it's not too bad, but it is a B tier rather than an A tier for the same reason as IBM.
It just depends on your situation. If you are already in a Microsoft heavy environment or targeting companies that run on Azure, then this one will give you the ROI that you're looking for. But if you're not in that world, AWS or Google credentials will get you further because those platforms are just more commonly used.
Now, you don't need to pursue all seven of these credentials that I've recommended. You just need to learn the right thing for where you want to head. Take the certification that matches your target company's tech stack and industry.
Commit to it and ignore everything else until you finish it. Trust me, I have been in that course taking rabbit hole where you just like hop on to the next course before you finish the last one. Don't do it.
I know it's tempting. Now, once you pick the right one for you, if you are looking for any other tech specific certifications to complement it, to really show employers that you can apply your AI skills to a specific industry focus, then I cover seven more certifications that can help you do that in this video.
