In the classroom
Data Structures, Statistical Inference and Introduction to Data Science — taught from first principles, with the notes published here so nobody falls behind for want of a handout.
I am Faqeer Hussain — a professor who never left the workshop. My lectures carry the habits of production software: careful structure, honest trade-offs, and code that has to survive contact with the real world.
Most syllabi describe software from a safe distance. Mine does not — because I spend my other hours writing it.
I teach at Government Graduate College, Layyah, where my students come from every kind of background — some with a laptop, many with only a phone. That reality shapes how I teach. Every course I run is designed so that a student with an Android device and an internet connection can complete it in full, without excuses and without expensive equipment.
Alongside teaching, I have years of hands-on experience building software that people actually use: websites that have to load on a weak connection, desktop applications that have to run all day without complaint, and mobile apps that have to feel right in the hand. That practice keeps my teaching honest.
So when I explain why an array is contiguous in memory, or why a confidence interval is not what most people think it is, I am not reciting a definition. I am telling you what it cost me to learn it properly.
Data Structures, Statistical Inference and Introduction to Data Science — taught from first principles, with the notes published here so nobody falls behind for want of a handout.
Full-stack web work, desktop software and mobile applications — delivered end to end, from the first sketch to the deployment that has to stay up.
Each course has its own permanent page. Bookmark the link for your course and check it through the term — notes, code and assignments are published there as we go.
How data is arranged in memory, and why that arrangement decides whether your program is instant or unbearable. Taught entirely in C++, starting with arrays.
Drawing defensible conclusions from incomplete data — estimation, confidence, hypothesis testing, and the honest limits of each.
From a raw, messy file to a conclusion someone can act on — the full pipeline, taught as a craft rather than a list of libraries.
Real projects, real constraints, real users. This is the experience I bring back into every class.
Marketing sites, portals and dashboards — designed for clarity, built to be fast on the connections people here actually have.
Tools for offices and institutions — record keeping, reporting and automation that has to work reliably, day after day.
Android applications built around how a phone is really used — offline-tolerant, light on data, and simple enough to hand to anyone.
They are simple, and they are the reason my students can still explain the material a year later.
If you cannot draw it on paper, you do not yet understand it. Definitions come last, not first.
Reading a program teaches you almost nothing. Typing it, breaking it, and fixing it teaches you everything.
A phone is enough. Every assignment I set can be completed on an Android device with a free app.
Miss a lecture and the notes are still here, on this site, for the whole semester and beyond.
Students: ask me during class or straight after a lecture — that is always the fastest answer. Everyone else: I am open to collaborations, guest lectures and software work, and can be reached through the college.