Context: Full Sail B.S. student + AWS intern documenting how I study. These tactics come from my Notion tracker, not an official training team.
AI assist: ChatGPT helped outline the sections and summarize Study Hall notes; I reconciled everything with my actual tracker on 2025-10-15.
Status: Early-career roadmap. Certifications prove I can learn, but they don’t replace production experience—so I pair every badge with a project.
Reality snapshot
- Active certs: AWS Solutions Architect – Associate (Aug 2024–Aug 2027) and AWS Certified AI Practitioner (Feb 2025–Feb 2028).
- Supporting coursework: freeCodeCamp JS Algorithms + Responsive Web Design, plus LinkedIn Learning soft skills (communication, GTD, personal branding).
- Tracker: Notion database with columns for domain, study hours, lab status, exam date, renewal reminders, and “paired project” (the thing I’ll build to prove it).
My study pipeline
1. Start with the exam guide
- Copy the official outline into Notion. I color-code each domain: green (confident), yellow (needs lab), red (needs deep dive).
- Add sample question links + whitepapers per domain. If I can’t explain the whitepaper to a friend, it stays red.
2. Plan the reps
| Practice type | Tools | Notes |
|---|
| Hands-on labs | AWS Skill Builder, Sandbox accounts | Spin up services, break them on purpose, then fix using CloudWatch + docs. |
| Flashcards | Anki decks per domain | Focus on limits, IAM condition keys, service integrations. Spaced repetition handles the rest. |
| Teach-backs | Loom recordings, study group | If I can’t explain a topic in 5 minutes, I haven’t learned it. I re-record after each round. |
| Mock exams | Tutorials Dojo, AWS practice tests | Take them cold once per week. Anything below 80% becomes next week’s lab. |
3. Pair a project with each badge
- SAA-C03: Built a Well-Architected checklist into Car-Match + the AWS internship capstone. Every section (Ops, Security, Reliability, Performance, Cost) gets a bullet in the repo README.
- AI Practitioner: Logged every Bedrock experiment (prompt templates, guardrails, cost estimates) in
notes/bedrock/. The goal wasn’t to become an ML engineer—just to show I can wire AI responsibly.
- freeCodeCamp certificates: Used the JS Algorithms work to refresh LeetCode patterns and the Responsive Web Design course to audit this portfolio’s layout.
4. Close the loop
- Retro doc: After each exam, I write a short postmortem: what worked, what didn’t, what to revisit in 3/6/12 months. Lives in
notes/certs/<exam>.md.
- Renewal reminders: Notion triggers at T-6 months, T-3 months, and T-1 month. Each reminder includes the “paired project” I’ll refresh (e.g., re-run cost optimization labs, rebuild a CI/CD pipeline).
- Public accountability: One LinkedIn post per milestone. Not for clout—just to keep friends/mentors in the loop.
Current roadmap
| Milestone | Target | Supporting project |
|---|
| AWS Developer Associate | Feb 2026 | Rebuild CheeseMath backend with AWS SAM + full test coverage. |
| AWS Security Specialty (stretch) | Late 2026 | Document IAM guardrails + incident drills for personal projects. |
| Zig + WebGPU deep dives | Ongoing | Expand Triangle Shader Lab and OBJ Parser with performance benchmarks + wasm builds. |
| Soft skills refresh | Quarterly | Run peer workshops on documentation, async updates, and honesty audits. |
Evidence & templates
Lessons learned
- The exam isn’t the finish line; the project you ship afterward is.
- Honest notes matter more than badges. Tracking energy, sleep, and morale kept me from cramming myself into burnout.
- Share the playbook. Letting classmates copy my Notion setup keeps us all accountable and surfaces gaps I missed.
References