👋 Introduction: The Start of a Long Journey
I’m starting something long-term, challenging, and ambitious: building the skills to become a Full-Stack Web Developer and AI Engineer from the ground up.
My background isn’t in computer science—I completed 12th-grade PCB (Physics, Chemistry, Biology)—so this is a complete transition into software development. I’m documenting the entire process publicly to create accountability, measure my progress, and eventually build a transparent, verifiable portfolio of work.
This is not a fast-track attempt or a pursuit of shortcuts. It’s a structured, multi-phase journey based on a detailed set of roadmaps. The goal is to understand both the fundamentals and the practical engineering skills required to build real AI-powered applications.
📢 Why I’m Learning in Public
My motivations are simple and practical:
- Accountability: Publishing my progress forces me to stay consistent and disciplined over months, not days.
- Clarity: Writing publicly helps me understand what I’m learning and why.
- Transparency: I want a portfolio that doesn’t just show final projects but the process behind them: the trade-offs, mistakes, and decisions.
- Community: By building openly, I can learn from others who have taken similar paths.
"This isn’t about building a personal brand. It’s about documenting reality—slow improvement over time, grounded in structured practice and honest reflection."
🗺️ The Road Ahead: My Learning Blueprint
My roadmap breaks the journey into clear, progressive phases. Each phase builds on the previous one and ends with a small but functional project to ensure the concepts are not just theoretical.
Phase 0: Foundations 🏗️
Before writing production code, I need underlying mental tools. This phase sets the base for both programming and future AI reasoning.
- Logic and computational thinking
- Basic statistics
- Foundational linear algebra concepts
- The core ideas behind how software works
Phase 1: Programming Fundamentals (Python) 🐍
Python is my starting point because it's widely used in backend development, automation, and AI systems.
- Syntax and control flow
- Data structures & error handling
- Writing clean, readable code
- Testing fundamentals
- Version control with Git
Phase 2: Frontend Development 🎨
To build end-to-end applications, I need to understand how users interact with software.
- HTML structure
- CSS layouts and responsive design
- Modern JavaScript
- React and eventually Next.js
Phase 3: Backend Development & Databases ⚙️
With frontend basics established, I’ll learn how real applications operate behind the scenes. This is where engineering habits form: structure, clarity, reliability, and maintainability.
- APIs and backend architecture (FastAPI or Express.js)
- Authentication flows
- Relational and NoSQL databases (PostgreSQL, MongoDB)
- Docker and containerization basics
Phase 4: Full-Stack Integration & Deployment 🚀
I’ll connect frontend, backend, and databases into functional systems.
- API consumption & user flows
- CI/CD fundamentals
- Deploying full-stack apps
Phase 5: AI & LLM Engineering 🤖
Once the full-stack foundation is solid, I’ll move into modern AI engineering. I’m focusing on integration and building real features with existing tools.
- Prompt design principles
- Embedding models & Vector databases
- Retrieval-Augmented Generation (RAG)
- Evaluating AI system performance
- Managing latency, cost, and context windows
Phase 6: Capstone Projects 🏆
Using everything above, I’ll design and build 3–5 full-stack AI-powered projects (e.g., a personalized RAG chatbot, workflow assistants). Each project will include a write-up explaining engineering choices, trade-offs, and limitations.
Phase 7: Portfolio & Career Prep 💼
Refining the portfolio, building case studies, and preparing for opportunities that match the skills proven through the projects.
📝 How I Will Document Everything
This is a learning-in-public journey with structured reporting. Here is what you can expect:
- Weekly Summaries: What I learned, what I built, what I struggled with, and what I improved.
- Public Code Repositories: Every phase will have its own folder, projects, and documentation.
- Deep Dives: Reflections on debugging issues, architecture decisions, and system diagrams.
My Starting Point (Week 1)
I’m currently beginning with:
- Setting up my development environment.
- Creating a structured learning log.
- Starting Phase 0 (Logic, Stats).
- Practicing Python fundamentals daily.
Closing Thoughts
This longform introduction marks the beginning of a disciplined, transparent, and technically grounded learning journey. I expect setbacks, slow progress at times, and difficult concepts—but I also expect steady improvement through deliberate practice.
If you’re on a similar path or have experience in full-stack or AI engineering, I’m always open to learning from others. But above all, this process is about accountability.
More updates to come.
— Arham Ghori
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