Data Scientist | Data Engineer | AI Enthusiast
Data Scientist | Data Engineer | AI Enthusiast
A comprehensive introductory course on Artificial Intelligence covering machine learning fundamentals, Python programming, and practical applications using TensorFlow, PyTorch, Pandas, and OpenCV.
Comprehensive program covering advanced AI topics such as deep learning, computer vision, and NLP. Included hands-on implementation of neural networks, transfer learning, and model evaluation.
A comprehensive program focused on developing strong skills in Artificial Intelligence and Machine Learning. The course covered Python programming, data analysis, deep learning and computer vision.
Provide enterprise-level technical support, managing critical incidents and service requests within SLAs. Leverage problem-solving skills to troubleshoot complex system issues, ensuring minimal downtime in a high-stakes corporate environment.
Instructed high school students in Python programming fundamentals, data structures, and algorithmic logic. Facilitated hands-on coding workshops, translating complex technical concepts into accessible learning modules.
Built and optimized ETL pipelines to process and clean 500GB+ Oracle database for analytics purposes. Developed executive-level dashboards in Power BI to support strategic decision-making. Designed an indoor navigation web application using Dijkstra’s algorithm. Collaborated in agile cross-functional teams and received a Certificate of Appreciation.
This project aims to develop a smart system that monitors water quality in real time by integrating Internet of Things (IoT) technologies with Artificial Intelligence (AI). The system uses multiple sensors connected to an Arduino board to collect environmental data, which is then processed, analyzed, and displayed in a user-friendly mobile application with AI-driven insights.
Authored a custom Python automation script to capture on-screen text and translate it in real-time. Implemented Computer Vision techniques using EasyOCR to accurately extract text from complex visual backgrounds.
Designed an interactive Power BI dashboard to visualize real estate transaction data across Saudi Arabia. Included dynamic maps, daily sales trends, and city-wise comparisons to support data-driven decision making.
Designed a Power BI dashboard to explore commercial registration data filtered by the year 2015. Visualizations included legal entity breakdowns, capital declarations, and registration trends to support regulatory insights.
Developed a deep-learning model using ResNet50V2 to classify sheep breeds from images, achieving 98.34% training accuracy. Techniques included data augmentation, class balancing, and transfer learning tailored for livestock image analysis.
Developing a machine learning project to detect fraudulent credit card transactions using multiple algorithms such as Logistic Regression, Random Forest, XGBoost, and LightGBM. The project focuses on handling imbalanced data, optimizing model performance, and providing clear visualizations for fraud analysis.
Saudi Arabia