Aws Serverless For Non-Coders Build Real Apps With Ai

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Aws Serverless For Non-Coders: Build Real Apps With Ai
Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 40m | Size: 3.64 GB
Direct ChatGPT & Claude to build real Lambda, API Gateway & DynamoDB apps. For AWS-certified pros who design, not code.
What you'll learn
Direct AI assistants (ChatGPT, Claude, Gemini) to generate, debug and deploy real AWS serverless infrastructure, without writing the code yourself.
Architect and ship a complete serverless application.
Catch the AI when it's confidently wrong.
Run the Build, Defend, Refactor loop.
Defend your architecture to a CISO, a CFO and an engineering manager in Role Play scenarios.
Design a DynamoDB single-table schema around real access patterns, then forecast its 12-month cost.
Diagnose real AWS failures with AI.
Launch your own quiz app on your own domain with CloudFront.
Requirements
AWS Solutions Architect Associate-level knowledge, or equivalent hands-on design experience. This is the floor, not a nice-to-have.
Comfort with the AWS Console, IAM roles, and the core services.
Enough Python to read code and question it.
A paid AI assistant, about $20/month (ChatGPT Plus, Claude Pro or Gemini Advanced). Free tiers produce weaker code that won't match the videos.
An AWS account. Everything you build fits inside Free Tier or a few dollars a month.
Commands are shown in Mac/Linux bash. On Windows, you'll ask your AI to translate them.
Description Build real AWS serverless applications (Lambda, API Gateway, DynamoDB) without writing the code yourself. You direct AI assistants like ChatGPT and Claude as your junior developer, you catch their mistakes, and you deploy everything on live AWS while staying the architect the whole way.
This hands-on course is built for the AWS-certified professional who can design a serverless architecture on a whiteboard but stalls the moment it's time to write the code.
You're not the problem. There is a real gap between designing a serverless system and implementing one, and most AWS courses pretend it isn't there. They either assume you already write Python fluently, or they hand you snippets to copy that teach you nothing about why they work.
This course closes that gap differently.The AI writes the code. You keep the decisions.
The mental model matters. The AI is your junior developer: fast, tireless, and confidently wrong just often enough that you can never ship its first answer. So your job isn't typing. You decide what to build, read what comes back, find the flaws, and defend the result in front of people who push back. That skill is genuinely scarce: 84% of developers already use AI assistants, yet fewer than a third say they trust the output. The professional who can validate what AI builds is the one every cloud team needs, and almost nobody is teaching it yet.
You'll watch real things fail, on purpose
Most courses show you the happy path. Here the errors stay in, because I hit them for real while recording, and fixing them on camera is where the learning happens
- The deploy banner that turnsgreen while your API is still broken, and how to stop trusting it
- ACORS error blocking your frontend, diagnosed and fixed by prompting the AI correctly
- A load test that comes back a mix of200, 429 and 503, and what each one is telling you
- IAM broken live into anAccessDenied, then repaired with least-privilege permissions
- A failed job landing in adead-letter queue while the alarm correctly stays silent, and why that silence is the right design
Along the way you'll pick up the Console-reality details most courses (and most AI assistants) get wrong: Create vs Deploy on HTTP APIs, TTL not being available at table creation, why WAF won't attach where you'd expect it. This is field knowledge, verified in the current Console, not recycled documentation. Catching your AI on exactly these points is half the method.
Not another "intro to Lambda" walkthrough
Over six modules plus a capstone you'll architect and deploy a complete serverless application on live AWS: Lambda, API Gateway, DynamoDB single-table design, S3 event triggers, SQS, SES, CloudFront and CloudWatch, all wired together, with every line of code generated by AI under your direction.
Every module runs the same loop, the one that separates professionals from tutorial-followers
-Build (Draft Zero). Get the AI to produce something that works, deploy it, and take the early win.
-Defend (Breaker). Then we break it. A traffic spike. An AWS bill. A least-privilege review. You'll see with real numbers why that first draft would fall over in production.
-Refactor. Go back to the AI with a focused prompt and fix the flaw. This is where it clicks that good prompting is iterative, not one lucky shot.
Between builds, you'll step into interactive Role Play scenarios: a CISO worried about a million-request attack, a CFO nervous about a runaway cloud bill, an engineering manager fresh out of a four-hour incident review. You don't just pick an architecture: you defend it with cost math and trade-offs, the way you'd have to in the actual meeting. Hands-on Udemy Labs environments are included, so you can practice in a sandbox before touching your own account.
Your capstone: a real app, on your domain, in your portfolio
Most courses end with a toy project you delete an hour later. This one ends with your own serverless quiz application, live on your own domain behind CloudFront. You pick the topic (Linux, Kubernetes, DevOps, anything you know well), you write the questions, you choose the branding. The architecture is the one you've been hardening all course; the content is yours. You finish with a live, public system you built and can point to at work or in an interview.
Read this before you enroll (the honest part)
This is a premium course for working professionals, and I'd rather lose a sale than earn a refund. So, plainly
-The first hour lays foundations so nobody gets left behind. If you already hold the SAA, watch it at 2x and treat it as your on-ramp: the new material starts as soon as you build in Module 1, and from there it doesn't let up.
-Budget about $20/month for a paid AI assistant. Free tiers produce weaker code that won't match what you see in the videos, and we'd rather tell you now than surprise you later.
-This is a doing course. Expect roughly 24 hours of hands-on building driven by short, focused video lessons. If you want something to watch passively on the train, this isn't it.
-Commands are Mac/Linux bash. On Windows, you'll paste them to your AI and ask for your shell's version. Not coincidentally, that's exactly the skill you're here to build.
-AWS costs stay tiny. The whole course, capstone included, fits inside the Free Tier or a few dollars a month, with cleanup checklists as you go.
Who this course is NOT for
Be honest with yourself here. It saves us both a refund
-Absolute AWS beginners. This is not a Cloud Practitioner course. You need Solutions Architect Associate-level knowledge (or equivalent hands-on design experience), because the Defend phases lean on it hard. Get certified first, then come back: the course will still be here.
-Aspiring developers. If your goal is to learn to write Python, take a Python course. Here you learn to direct the AI, not to replace it.
-Anyone unwilling to pay about $20/month for a proper AI assistant. It's a tool of the trade here, like the AWS account itself.
-Passive watchers. You build, break and fix something in every single module. If you won't open the AWS Console and get your hands dirty, you'll capture a fraction of the value.
-Fluent serverless developers. If you already write and deploy Lambda code every day, the AWS content will be familiar. You'd be here only for the AI-direction method.
Why learn this from me
I'm Alessio Ferrari: AWS Certified Solutions Architect, 20+ years in IT, and over 12,000 students across 14 Udemy courses. Udemy selected and funded this course through itsContent Innovation Fund, which backs new formats in online learning. Here, the format is the method itself: AI not as a topic on a slide, but as a tool you learn to direct inside every hands-on exercise.
Training a team? The Build, Defend, Refactor loop is the same workflow senior engineers use with AI today. It gives sysadmins, PMs and junior architects a safe, repeatable way to prototype on AWS before a dev team gets involved.
What you actually walk away with
The quiz app you build will date. The skill behind it won't. By the end you won't be thinking "I deployed a quiz on AWS." You'll be thinking"I can direct AI to build serverless infrastructure whenever I need it." That's the skill worth having, and the window to learn it before everyone else is now.
You bring the architecture decisions. The AI does the typing. Let's build something real.
Enroll now and ship your first AI-built AWS serverless app this week.
Who this course is for
AWS-certified (or certifying) professionals (sysadmins, IT managers, Solutions Architects) who can design serverless systems but stall at implementation.
SAA holders who want to turn certification knowledge into a live, deployed application they can show at work.
IT managers and team leads who need to prototype and validate architectures before involving a dev team.
Mid-career cloud professionals who want a rigorous, validation-first way to build with AI, not vibe coding and hoping.
Anyone tired of passive video courses who wants to build something real on live AWS with AI as their developer.

Code:

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