class FarhanUddin:
def __init__(self):
self.name = "Mohammed Farhan Uddin"
self.role = "Python Full-Stack Developer"
self.location = "Hyderabad, India 🇮🇳"
self.education = "B.Tech CSE @ MRIT (2021-2025)"
self.email = "mohdfarhanuddin002@gmail.com"
@property
def currently(self):
return [
"🔨 Building scalable REST APIs",
"📖 Mastering FastAPI + Django",
"☁️ Exploring AWS Architecture",
"🤖 Working on AI-powered backends",
]
@property
def ask_me_about(self):
return ["Python", "FastAPI", "REST APIs",
"MySQL", "Backend Design"]
def __str__(self):
return "Clean code. Fast APIs. Zero excuses." |
|
🛍️ Madam Choice Footwear — Full-Stack E-Commerce App
Stack:
FastAPIMySQLHTMLCSSBootstrap| 🌐 Live Site
| Metric | Result |
|---|---|
| 🗃️ Products Managed | 50+ records with real-time cart & order tracking |
| ⚡ API Response Time | Reduced by 35% via efficient routing & middleware |
| 🔍 Database Speed | Improved by 40% via indexed SQL optimization |
| 📱 Page Load Time | Reduced by 30% with mobile-first Bootstrap UI |
| 🔌 REST APIs Built | 10+ covering auth, products, orders |
💰 Expense Tracker Application — Backend System
Stack:
FastAPIMySQLREST APIsPython
| Metric | Result |
|---|---|
| 📊 Transactions Handled | 100+ with multi-category filtering |
| ⏱️ API Response Time | Consistent sub-200ms across all endpoints |
| ✅ Uptime During Testing | 99% — zero downtime |
| 🤖 Manual Effort Saved | 60% via automated report generation |
| 🗄️ Data Redundancy | Reduced by 45% with normalized schema |
🤖 Assessment Recommendation Engine — AI Backend
Stack:
FastAPISemantic SearchPythonML
| Metric | Result |
|---|---|
| 🎯 Relevance Accuracy | 85%+ using semantic search |
| ⚡ Response Time | Reduced by 50% via caching & pre-processing |
| 📦 Data Processed | 1,000+ records cleaned and structured |
| 📈 Recommendation Precision | Improved by 30% over keyword-matching baseline |
🔐 Cybersecurity Threat Detection — ML System
Stack:
PythonMachine LearningFeature EngineeringEnsemble Methods
| Metric | Result |
|---|---|
| 🎯 Detection Accuracy | 92% on validation datasets |
| 🗂️ Records Processed | 5,000+ network activity records |
| 📉 Feature Dimensionality | Reduced by 35% without performance loss |
| 🛡️ False Positive Rate | Reduced by 28% via hyperparameter tuning |
📱 QGS Workforce Management App — Full-Stack Mobile + Backend
Stack:
FastAPIPythonMySQLREST APIsAndroid APK| 📲 Download APK Demo
End-to-end workforce management system built for Qanat Global Solutions with 4 fully role-based dashboards — Admin, Supervisor, Team Leader & Participant (Worker).
| Metric | Result |
|---|---|
| 🧑💼 Role Dashboards | 4 — Admin, Supervisor, Team Leader, Participant |
| 👥 Workforce Scale | 5,000+ active workers managed |
| ✅ Features Shipped | Attendance, QC Checks, Production tracking, Check-in/out |
| 📊 QC System | Excel upload for QC results, auto-grading & level progression |
| 💳 Extra Modules | Payments, Fraud Detection, Role-based Login/Logout |
| 🔐 Auth Coverage | 100% — secure sign-in/sign-out for all 4 roles |
🌐 QGS Corporate Website — Full-Stack Web
Stack:
HTMLCSSJavaScriptVercel| 🌐 Live Site
Corporate website for Qanat Global Solutions — an AI data infrastructure company powering lead generation, transcription, data extraction, and voice projects globally.
| Metric | Result |
|---|---|
| 🌍 Global Reach | 150+ countries covered |
| 🗄️ B2B Contacts | 214M+ verified first-party professionals |
| 👨💻 Workforce Represented | 5,000+ trained human data workers |
| 📉 Avg CPL Reduction | 40% below industry benchmark |
| 🏆 Certificate | 🏢 Issuer | 📅 Year |
|---|---|---|
| ☁️ AWS APAC Solutions Architecture | Forage | 2026 |
| 🤖 Retrieval-Augmented Generation for AI | IBM SkillsBuild | 2025 |
| 🐍 Python Programming Fundamentals | HackerRank | 2025 |
| 🏛️ Aspire Leaders Program — Harvard Business School Design | Aspire Institute | 2026 |
