Computer Science graduate passionate about Artificial Intelligence, Data Analytics, Machine Learning, and building intelligent systems that solve real-world business problems through data-driven decisions.
GPA
Projects
Computer Science graduate from King Abdulaziz University (GPA 4.9/5) with First-Class Honors with Distinction. Passionate about Artificial Intelligence, Machine Learning, Data Analytics, and intelligent systems development. Experienced in building dashboards, analyzing large-scale datasets, and developing AI-powered solutions including financial auditing automation, predictive modeling, and operational analytics. Worked with real enterprise datasets and delivered AI-driven training programs at Petromin Corporation.
Senior capstone project at KAU. AI-powered auditing system automating reconciliation, VAT validation, duplicate detection, and OCR invoice matching. Tested on 500+ invoices with 96.6% matching accuracy and 0 VAT errors. Built as a full web application with authentication and live dashboards.
View on GitHubEnd-to-end ETL pipeline simulating a real-world retail data engineering workflow. Extracts, validates, cleans, and transforms synthetic retail sales data, then loads it into a relational SQLite database with SQL views and analysis queries — built with a modular, production-style project structure.
View on GitHubML classification system processing 7 datasets with 32K+ student records and 10M+ interaction logs. Applied SMOTE, feature engineering, and trained Random Forest (85%) and Logistic Regression (82%) models. Deployed as a real-time Streamlit prediction app with confidence scoring.
View on GitHubAnalyzed 5.8M+ flight records to identify delay causes, seasonal trends, airline performance, and airport efficiency. Built interactive Power BI dashboards supporting operational insights and scheduling optimization.
View on GitHubDesigned a university library SQL database with 10+ tables, 15+ relationships, ERD modeling, 3NF normalization, and advanced SQL queries using real sample data.
View on GitHubAnalyzed 5,573+ sales and purchasing transactions across 5 branches to uncover pricing trends, evaluate business performance, and support strategic decision-making.
Performed data cleaning and exploratory data analysis (EDA), and developed 5 Power BI dashboards that transformed raw data into KPI-driven insights for university stakeholders.
Delivered AI productivity training to 900+ employees across multiple departments, introducing 50+ AI tools to enhance efficiency, automation, and digital adoption.
Simplified technical and academic concepts for 110+ subscribers, helping learners improve their understanding of programming, algorithms, data structures, and mathematics.
Advanced deep learning training focused on CNN architectures, image preprocessing, convolutional layers, pooling, and AI model development for computer vision tasks.
National Talent Development Program covering machine learning fundamentals, AI concepts, predictive systems, and intelligent technologies through structured coursework.
Official engineering membership recognized by the Saudi Council of Engineers. Credential ID: 1255174. Valid Jun 2026 – Jun 2027.
Verify MembershipKAUST Academy program covering Python fundamentals as AI prerequisites — powered by University of Michigan via Coursera. Completed all 5 courses with verified certificates.
Completed 3 full learning paths covering data preparation, DAX in semantic models, and effective report design — core foundation of the Microsoft PL-300 certification path.
Specialization covering the full mathematical foundation for ML and Data Science — taught by Luis Serrano via Coursera. Completed all 3 courses with verified certificates.
Completed the AI academic track at KAU covering core AI principles, machine learning models, data analysis methods, and applied AI problem-solving techniques.
Advanced programming track at KAU covering software engineering principles, algorithms, data structures, and problem-solving using modern programming paradigms.
Awarded the Certificate of Excellence for maintaining a GPA of 4.9/5 across 5 consecutive academic years (2021–2026) at the Faculty of Computing and Information Technology.