My AI Learning Journey
How I went from writing my first Python loop to building AI-assisted projects — the detours, the habits that stuck, and what I'd do differently.
Computer Science student with a strong passion for Artificial Intelligence, programming, and modern technology. My goal is to become a professional AI Engineer and contribute to intelligent systems that create real impact.
Curious about intelligent systems, passionate about clean code, and always learning.

Fascinated by intelligent systems and how they reshape the world.
Breaking down complex problems into elegant, working code.
Always exploring new tools, papers, and technologies.
Collaborate clearly, communicate openly, ship together.
Building things that feel new — not just re-hashed patterns.
Clean, readable, maintainable code as a personal standard.
From the fundamentals to computer science at UET Lahore.
Focusing on AI, algorithms, and modern software engineering.
Mathematics, Physics, and Computer Science foundations.
Science group with early curiosity for computers.
Languages, tools, and soft skills I use to build and collaborate.
Every project ships with a runnable live demo and its real source code — open any card to try it.
Adaptive signal controller that reads live queue lengths at every approach and allocates green time to the most congested one instead of a fixed timer.
Automated traffic violation and challan management with fine calculation, payment tracking and database-backed records.
Shortest word-transformation solver using breadth-first search over a dictionary graph — try any two four-letter words.
Classic game with a minimax opponent that never loses. Play the live version below — the best you can get is a draw.
CRUD application for student records with persistent file handling plus live search and merit-order sorting.
Internships and coursework across Python, generative AI, and prompt engineering. Click any certificate to view it full size.
Notes on AI, Python, and the craft of learning technology.
How I went from writing my first Python loop to building AI-assisted projects — the detours, the habits that stuck, and what I'd do differently.
Small habits and language features that quietly made my Python cleaner, faster, and much easier to debug.
Five buildable projects that teach real AI concepts — ordered from a weekend afternoon to a serious portfolio piece.
What actually improves model output in real work: structure, constraints, examples, and evaluation — not magic words.
A place for future collaborators, mentors, and teammates to share thoughts.
Testimonials coming soon — reserved for real recommendations.
Open to internships, collaborations, and interesting AI conversations.