Abdul Rahman Azam – Full Stack AI Engineer
Abdul Rahman Azam is a Full Stack AI Engineer from Karachi, Pakistan, specializing in machine learning, deep learning, and modern web development with React, Node.js, and Python. He is currently pursuing a BS in Artificial Intelligence at FAST NUCES Karachi with a CGPA of 3.33.
About Abdul Rahman Azam
Abdul Rahman Azam builds AI-powered web applications that combine machine learning models with full-stack engineering. His projects include an Income Prediction System achieving 85% accuracy on 32,000+ census records, a Super Tic-Tac-Toe AI with Minimax and Alpha-Beta Pruning, and a University Resource Sharing Platform built with React, Node.js, and PostgreSQL. He has solved 290+ LeetCode problems, earned 6 skill badges, and holds HackerRank Problem Solving certifications at both Basic and Intermediate levels.
Skills & Technical Expertise
Web Development: React.js, Node.js, Express.js, JavaScript, Tailwind CSS, PostgreSQL, REST APIs
AI/ML & Data Science: Python, Machine Learning, Deep Learning, Scikit-learn, Pandas & NumPy, Data Visualization
Projects by Abdul Rahman Azam
University Resource Sharing Platform (Jan – May 2025)
Full-stack university platform for resource sharing, community discussions, and moderated student collaboration. Technologies: React, Node.js, PostgreSQL, REST APIs. Role-based authentication and admin moderation. Scalable relational database architecture.
Super Tic-Tac-Toe AI Game (Apr – May 2025)
Web-based 9×9 Super Tic-Tac-Toe with intelligent decision-making and multi-board scoring. Technologies: JavaScript, Game AI, Minimax. Minimax with Alpha-Beta Pruning optimization. Complex multi-board game-state evaluation.
Income Prediction System (Sep – Dec 2024)
Machine learning system for income prediction using large-scale census data. Technologies: Python, Machine Learning, FastAPI. 85% accuracy on 32K+ real-world records. Interactive analytics with multiple model variants.
2D Action Platformer Game (Feb – May 2024)
High-performance 2D action platformer with advanced enemy behavior and weapon systems. Technologies: C++, Game Development, OOP. Top 1% university project for creativity. Advanced collision and physics handling.
Unbeatable Tic-Tac-Toe AI (Sep – Dec 2023)
Perfect-play Tic-Tac-Toe AI based on deterministic game theory. Technologies: C, Algorithms, Game Theory. Provably optimal Minimax strategy. Multiple gameplay modes supported.
Education
BS in Artificial Intelligence – FAST NUCES Karachi (2021 - Present) – CGPA: 3.33
Intermediate in Pre-Engineering – Adamjee Govt. College (2019 - 2021) – 80%
Matric in Computer Science – Happy Palace School (2017 - 2019) – 98.12%
Achievements & Certifications
LeetCode Achievement: Solved 290+ problems on LeetCode and earned 6 skill badges, strengthening algorithms and data structures.
Competition Success: Secured 2nd Place in Web Hunt Competition and 3rd Place in ACM Coders Cup.
HackerRank Certifications: Achieved Problem Solving – Basic & Intermediate certifications on HackerRank.
ChatGPT Certification: Completed ChatGPT for Everyone (Learn Prompting) certification.
Contact Abdul Rahman Azam
Email: azamabdulrahman930@gmail.com
GitHub: https://github.com/abdulrahmanazam
LinkedIn: https://linkedin.com/in/abdulrahmanazam
LeetCode: https://leetcode.com/abdulrahmanazam
Website: https://abdulrahmanazam.me