A growing collection of hands-on AWS Cloud & AI/ML projects. Built to learn, test, and showcase real-world skills.
Welcome to my evolving footprint in the world of AWS Cloud and Artificial Intelligence.
This repository is where I build, test, and showcase real-world projects — one command, one service, and one model at a time. Every line of code reflects what I’ve learned hands-on from AWS tools, AI/ML workflows, and Python automation.
I’m 48 years old, and this is the second chapter of my career — a deep dive into AI, cloud, and the power of lifelong learning.
My fascination with AI began when LLMs became publicly available. I wasn’t the “technical” person at the time, but I was drawn to how accessible AI made learning — how it felt like a window into your soul without judgment. AI became my teacher, motivator, and study partner — not a shortcut, but a guide.
Over the past year, I’ve studied relentlessly through Coursera and beyond:
- 🎓 Prompt Engineering Specialization (Vanderbilt University)
- 🐍 Python for Everybody (University of Michigan – 4 courses)
- 🧠 AI Foundations (IBM – 3 courses)
- 🧬 Deep Learning Specialization (Stanford – Prof. Andrew Ng)
- ☁️ AWS Cloud & AI/ML Certification Prep
- Currently building a 545-page AI/ML study guide: “The AI/ML Bible”
I’ve also explored cloud computing and am pursuing both the Cloud Practitioner and ML Specialty certifications from AWS.
Alongside studying, I started building:
- 🧱 Custom VPC + EC2 + Docker Setup — a full AWS environment from scratch
- 🤖 Sentiment Analysis AI Agent using CrewAI, hardcoded from scratch
- 🪄 No-code Multi-Agent Workflows using n8n + OpenAI
- 📘 The AI/ML Bible — a structured, living document I will upload and open-source here
Now, I’m focused on cloning real AWS GitHub repos, breaking them down, rebuilding them from scratch, and documenting everything. My mission is simple: Learn by building. Build to grow. Share to inspire.
| Project Name | Description |
|---|---|
| AWS VPC Setup | Build a secure Virtual Private Cloud with subnets, routing, and security groups |
| EC2 Web Server | Launch a Linux instance, install a web server, and access it via SSH |
| Docker → ECS | Create a Docker container, push to Docker Hub, and deploy to AWS ECS |
| AI/ML Bible Upload | Clean, organize, and publish my 545-page study guide for the community |
- AWS (VPC, EC2, ECS, SageMaker, Bedrock)
- Docker, GitHub, VS Code
- Python, Bash, YAML, Markdown
- OpenAI, n8n, CrewAI
I don’t just study AI/Cloud — I build it.
This repo is my Nova — a star rising from curiosity, discipline, and the belief that it's never too late to learn.
Let’s build. 🔥