Projects · 1 flagship + 5 AWS builds

Ship one real app, end to end.

Not a tutorial you follow — an application you own. CineList runs on a live dev server with a real IDE; each module is verified before the next unlocks. When it's deployed, it goes on your resume with a link that works.

Start module 1~7 hours total. Pick it up where you left off.

Projects / CineList8 modules · ~7 hlive dev server

Build the screens Reactverified

Multi-page app React Routerverified

Build the API Node + Expressverified

Connect front & back fetchverified

Add a database MongoDBverified

Image uploads Multerin progress

Deploy it live Dockernext

https://m7-7f21.vm.deployu.ai:5173 module 7

CineListPOST /api/movies/42/poster · 201

Module 7 · Image uploads

What a module actually asks of you.

Each module is 45–60 minutes with four to six verified tasks. This one: accept a real image with Multer, store it, serve it, show it in the React UI. The verifier uploads a file through your endpoint and checks it comes back.

task 3 / 5 server/routes/movies.js

1const upload = multer({ dest: 'uploads/', limits: { fileSize: 2e6 } })

3router.patch('/:id/poster', auth, upload.single('poster'), async (req, res) => {

4 const movie = await Movie.findByIdAndUpdate(req.params.id,

5 { poster: `/uploads/${req.file.filename}` }, { new: true })

6 res.status(201).json(movie)

7})

You write it in the real projectThe whole repo is there — your modules 1–6 code, not a fresh starter.

verify module 7 · task 3

PATCH /api/movies/:id/poster accepts multipartuploaded fixture.png (180 KB)

pass

Response 201 with poster path/uploads/5f1c…png

pass

File is served backGET /uploads/5f1c…png → 200, image/png

pass

Rejects > 2 MB413 on 3 MB fixture

pass

Checked by doing, not by reading your codeThe verifier exercises your running server. Style doesn't matter; behaviour does.

Project labs

Five one-sitting builds on a real AWS account.

Smaller in scope, still resume-worthy. Each one ends with something running that you can screenshot, link or demo.

AI · Bedrock

RAG chatbot on Amazon Bedrock

7 tasks1 h 30

Knowledge base, embeddings, a chat endpoint that cites sources.

Storage & CDN

Static site on S3 + CloudFront

6 tasks1 h

Bucket policy, website config, a CDN with HTTPS in front.

Networking

Auto-scaling fleet behind an ALB

8 tasks2 h

Launch template, target group, scaling policy you can watch fire.

AI · Rekognition

Identity verification with Rekognition

6 tasks1 h

Face comparison behind a Lambda and API Gateway.

AI · Bedrock

Content moderation pipeline

6 tasks1 h

S3 event → Lambda → Bedrock classification → tagged object.

Your resume needs one real link. Build it here.

Start module 1