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AWS Skill Builder Free vs Paid: Is the Subscription Worth It?

Julius Akeem De Leon — Tue, 30 Jun 2026 14:50:27 +0000

One of the first things that crossed my mind when I opened AWS Skill Builder was a simple question: what exactly is the difference between the free version and the paid one? It started when I was trying to access AWS Cloud Quest. I couldn't get into it on my own, but once I had the subscription, it opened up. That moment made me curious. If just having Skill Builder unlocked something like Cloud Quest, what else was I missing? What does the paid tier actually give you that the free one doesn't? So I went exploring, and this is what I found.

The Free Tier: More Than You'd Expect

Being on the free tier is not really a disadvantage because with AWS Skill Builder's free tier, you can already explore and access over 600 free courses, which is pretty good on its own considering the amount of possibilities you can explore across a wide range of AWS services, from foundational cloud concepts to more specific topics like security, storage, and machine learning.

Personally, I've already had great experiences with the free tier, and it is pretty much a great starting point if you want to explore what AWS can offer, especially when you're preparing for certifications like AWS Cloud Practitioner for example. But the further you go into your AWS learning journey, the more you start noticing what's locked behind the paid subscription.

Where the Free Tier Shows Its Limits

There's this one course called "AWS Cloud Quest: Generative AI Architect" and I got specific interest in this course because I wanted to master the integration of generative AI capabilities which can be turned to solution deliveries, but the problem is that I wouldn't be able to access its 27 hands-on assignments inside that course because it is available only with the Skill Builder subscription, and the course content itself is also locked behind it.

As you can see in the screenshot above, there are certain learning paths that were locked and you cannot access with the free tier alone. Most hands-on labs require a subscription, and some of the more structured role-based learning experiences are simply unavailable without upgrading.

But once I had the subscription, the difference was immediately visible. I went straight back to AWS Cloud Quest: Generative AI Architect, and this time the full course opened up after I enrolled, with all 27 hands-on assignments now accessible.

What the Paid Tier Actually Unlocks

The paid tier in this course grants you access to a comprehensive curriculum that moves from cloud and Generative AI fundamentals directly into advanced AWS architecture. Instead of just giving you theoretical concepts, it focuses heavily on deployment and security. You'll master core AI engineering skills, including prompt engineering with Amazon Bedrock, model fine-tuning and automation on Amazon SageMaker (including RLHF), and application development using LangChain and vector databases.

Through the hands-on labs, you get to build and secure a variety of production-ready AI tools, such as private serverless chatbots, intelligent multi-media Q&A applications, automated content moderators, and even tailored solutions for industries like marketing and education.

What I liked about this is that the course doesn't throw you into the deep end right away. It eases you in, starting from cloud basics before gradually moving into the heavier topics like fine-tuning, prompt engineering, and deploying LLM agents.

How Much Does It Cost?

Of course, when you purchase an AWS Skill Builder subscription, you can either pay $29/month or $449/year.

If you have a genuine interest in exploring AWS in depth, or you're planning to take a certification exam in the near future, I'd recommend going with the annual plan. With it, you get access to AWS Certification Official Practice Questions that mirror the style and depth of the actual exams, plus select exam prep courses that help build your confidence going into exam day. But if you're just casually exploring AWS, want to get a feel for the subscription before committing annually, or simply want full access to the course content, the $29/month plan is a solid entry point. It already gives you a clear sense of which direction you want to go and which areas of AWS you're most drawn to.

So, Is It Worth It?

Personally, both tiers are good depending on where you are in your AWS journey. If you're trying to get a feel for what AWS Skill Builder offers before committing to a payment, I'd recommend starting with the free tier first.

Despite its limitations, you're already getting access to meaningful content, especially when it comes to digital courses, microcredentials, and classroom trainings.

But when you move to the paid subscription, you unlock a much wider variety of experiences like AWS Cloud Quests, Industry Quests, SimuLearn, and more, which becomes a real advantage if you're exploring a topic in depth or actively preparing for a certification exam.

Who Should Stay on the Free Tier

The free tier is great for learning the basics. You should stay on the free tier if you are:

A beginner: You are just starting out and want to learn basic cloud concepts.
Focused on videos and reading: You prefer watching digital courses instead of doing hands-on labs.
Using your own AWS account: You are comfortable practicing in your own AWS Free Tier account and making sure you don't get billed.
Trying it out: You want to see how the platform works and earn basic badges before paying.

Who Should Consider Subscribing

The subscription gives you live practice environments and official exam prep. You should upgrade if you are:

Getting certified: You are studying for AWS exams and want to take the Official AWS Practice Exams.
A hands-on learner: You want to use AWS Builder Labs. This gives you a safe, temporary AWS account to practice in, so you do not risk charging your own credit card.
Learning through games: You want full access to all roles in AWS Cloud Quest and want to solve problems in AWS Jam Journeys.
Doing advanced work: You already know the basics and need step-by-step help building complex AWS setups.

For students and community builders alike, Skill Builder is one of those resources that grows with you. Start where you are, and upgrade when you're ready.

"I Failed My Way Into Leading a part of a Tech Community"

MJ Medina — Tue, 30 Jun 2026 12:58:04 +0000

If you saw the banner and title, you'd probably assume I had this all figured out.

I've been in college for six years now. I still remember the exact moment a thought popped into my head and refused to leave: "The tech industry is so diverse, the market so saturated—how does someone like me, with failing grades, no technical skills, and no clear niche, even begin to find his place in it?"

actual cropped pictures of my failing grades

Far from motivating me, that thought did the opposite—it left me anxious and directionless, filling my time with things that didn't matter, doing everything except preparing myself for a competitive industry that would eat me alive if I didn't try. Part of me convinced myself I already knew enough. Liking tech was innate in me, but I couldn't do anything to create tech with my own hands. Sit me down in front of a laptop, and I'd find myself staring at a blank IDE, cursor blinking, not knowing what to write because I didn't really know what I wanted to create.

And then, somehow, in the middle of all that, I ended up at an AWS Cloud Club workshop event. I didn't go in with a plan—I just wanted to try, because I had nothing else to lose. Maybe my anxiety pushed me into it. Frankly, I had fun. Building a project from scratch, getting introduced to software technologies I had no idea existed, writing code again—all of it sparked a curiosity in me I hadn't felt in a long time.

My very first AWS Cloud Club Workshop

It was those same people who sparked my curiosity that opened a door to an opportunity I could grab—to lead a department within AWS Skillbuilder. I thought to myself that maybe this was a worthy shot: a chance to reclaim my motivation, to actually have something to stand for and be determined about in the world of tech, to start learning different technologies, and maybe, along the way, to focus on my academics too.

Landing the role of Data Science Lead for Skillbuilder came before I actually knew how to be one, that's how I started teaching myself through self-paced workshops with NextWork and the AWS Skill Builder(Website). Those workshops were an eye-opener: I realized I knew almost nothing compared to what I'd believed about myself. At first it was overwhelming because I was entering a new world I haven't been to, but the labs and projects were straightforward and thoroughly explained step-by-step. I gathered as much knowledge as I could to prepare myself to host events and build projects using the AWS console, sharing what I learned with our community and actually getting them hands-on with different AWS services.

Skillbuilder events hosted by AWS Cloud Club Adamson University (Now AWS Student Builder Group Adamson University) in which I spoke.

Skillbuilder events hosted by AWS Cloud Club Adamson University (Now AWS Student Builder Group Adamson University) in which I spoke." width="800" height="419">

Even then, it wasn't easy. I'd spend hours retracing notes, just to make sure I could explain things clearly to someone else the next day. But somewhere in that repetition, the thing I used to dread—sitting in front of a blank screen, not knowing what to build—started turning into something I looked forward to. Not because I'd gotten good at it, but because I finally had a reason to keep trying.

Day by day, things started to shift. My grades actually got better—not because school suddenly became easy, but because I finally had a reason to care about what I was learning. I started taking on projects of my own, even landed a few clients to build software for—something I never thought I'd be capable of just a few years prior. I began showing up more, not just to AWS events, but to tech communities in general, proactively looking for ways to learn and contribute instead of waiting for opportunities to find me. Looking back, that's where it really started: the grit, the determination, the curiosity, the hunger to learn that I didn't know I had in me until I gave myself a reason to use it.

Projects I've developed so far (some with collaborators)

(Read the first letters of each paragraph starting at the top) But now, I'm a Skillbuilder Director, still trying his best to prove that those six letters were never the end of my story—just where it began.

I'd like to thank everyone who paved the way for me in this direction, from my peers within the AWS SBG Adamson Community, the AWS User Groups, AWS Skillbuilder, AWS E:novators, and the whole AWS Community. Thank you for showing me so much more, allowing me to collaborate, learn, and teach the community too.

I'm MJ Medina from Adamson University, how about you? where do you find your determination?

Launching EC2 Instances Across AZs: My First Skill Builder Lab

Mervyn Mario Simons — Tue, 30 Jun 2026 12:09:12 +0000

Hello fellow builders! I'm an incoming 4th year BSCS student specializing in data science. I am the incoming Data Science lead for AWSBG at Adamson so this role will involve helping other students learn AWS and cloud computing.

When the Skill Builder execution workshop came up, I saw it as a great opportunity to finally get hands-on experience. Not just for myself, but so I could actually use this for future workshops and teach other students better.

So I picked a lab and just went for it. Here's how it went.

The Lab

The lab was titled "Cloud First Steps" and the goal was simple: launch two EC2 instances in different Availability Zones within the same AWS Region.

EC2 is basically virtual computers in the cloud. Availability Zones are just different physical locations where AWS has data centers. So you're running two servers in two different places so if one location has issues, your stuff doesn't just die.

The region I used was us-east-1 (N. Virginia) since that is what the lab suggested. Here is what I did in the Lab:

Step 1: First Instance

The lab walked me through launching the first one. I went to the EC2 dashboard, clicked "Launch Instance", picked t3.micro (the free tier one), selected us-east-1a as the zone, and hit launch.
That was it. Took maybe 3 minutes. Instance was up and running.
I named it webserver01 so I wouldn't forget what it was for.

Step 2: Second Instance (The DIY Part)

This was where I had to figure things out on my own. I had to launch a second instance in a different zone.
Honestly? Pretty straightforward. I just clicked "Launch Instance" again, used the same AMI and instance type, but this time manually selected us-east-1b from the dropdown.
Named it webserver02.
The console felt familiar honestly. It's not that different from any other workspace or IDE I've used before. The layout made sense. Buttons were where I expected them to be. I didn't feel lost or overwhelmed.

Step 3: Validation

The lab had a built-in validation system that checked if both instances were running in separate zones. I just clicked the button and it verified everything.
Then I got this screen:
"YOU DID IT!"
Showed my instance ID i-0004924225b4793f0 and confirmed both instances were in separate zones.

What I Actually Learned

I knew what AZs were from studying but actually seeing my instances in us-east-1a and us-east-1b made it real. These are actual different data centers. If one goes down, the other keeps running.
t3.micro is free tier, I used it for both instances. Didn't get charged anything so its good for practicing.
Launching instances is actually really fast, I thought it would be more complicated.

Why This Matters for Teaching Especially For My Role

One of the main reasons I wanted to do this lab was so I can use what I learn for future AWS workshops at school. I want to help build cloud skills in my school community and actually teach people.

This lab gave me a concrete example to show students. When I explain EC2 and Availability Zones, I can say "here's what I did, here's how it looked, here's what I learned."

Plus it helps me understand the learning experience from a student perspective. What's confusing? What's straightforward? What mistakes do people make? Now I actually know because I went through it myself. Which is way more valuable than just reading documentation.

My Key Takeaways for Beginners

Honestly, Just start. Don't overthink it and explore. But here are some tips specifically about this Lab.

Use proper naming conventions because if you have two instances both unnamed, you'll get confused. Simple names like webserver01 and webserver02 work fine.
Check your Availability Zone. It's easy to accidentally launch both in the same zone. Double check the dropdown before you click launch.
Your instance isn't fully ready until the status check passes. "Initializing" is normal.

Final Thoughts

Being from India, I want to share with one of my favorite quotes from our national hero: Mahatma Gandhi.

"Live as if you were to die tomorrow. Learn as if you were to live forever." — Mahatma Gandhi

That really sums up how I feel about AWS and the tech world in general. There's always something new to discover, always another lab to run, always another skill to build. One lab done, but the learning definitely doesn't stop here.

So I'm gonna keep going through Skill Builder labs. I'm currently finishing up the "AWS SimuLearn: Generative AI Architect" learning plan. So still a lot to learn! I want to build up enough experience so I can confidently run workshops and help other students at my school learn AWS.