Data Scientist
Recent graduate with a Bachelor's degree in Informatics and Computer Science, specializing in Artificial Intelligence, from The British University in Egypt and London South Bank University. Experienced in data management, processing, and analysis with a focus on optimizing pipelines and enhancing data quality. Proficient in Apache Spark, SQL, and NoSQL. Committed to continuous learning and collaboration across teams.
During my tenure as a Front End Web Developer Trainee at ITICS, I gained hands-on experience in crafting tailored solutions using HTML, CSS, JavaScript, and Python. This opportunity honed my skills in front-end development and provided valuable insights into practical web technologies.
As a Data Science & AI Intern at SYNC Interns, I had the privilege of applying theoretical knowledge to real-world projects, under the mentorship of Naveen Kumar and the SYNC Interns Team. This experience fortified my skills in data science and AI, preparing me for future endeavors.
Furthermore, my roles as a Machine Learning Intern at both Mentorness and TechnoHacks EduTech provided dynamic experiences involving hands-on projects and real-world applications. These internships deepened my understanding of machine learning and data analysis, enhancing my ability to tackle complex problems.
My involvement in various projects, such as Anomaly Detection in a Cavitational Desalination Pump and Sentiment Analysis Model for Women's Clothes E-commerce Reviews, demonstrates my capability to conduct research and develop practical solutions using advanced techniques.
Additionally, I have showcased my creativity and technical prowess through game development projects like "The Code of Treasures" and "The Life of a Miner in Congo," as well as contributions to software quality assurance initiatives.
I am eager to leverage my diverse experiences and skills in a dynamic environment, contributing to innovative projects and driving impactful decisions.
Good in Artificial Intelligence
The British University in Egypt
Graduated: 28/07/2022
Second Class Honours (1st division) in Artificial Intelligence
London South Bank University
Graduated: 06/07/2022
Cairo, Egypt · On site
01/09/2018 - 01/12/2018
Mirzapur, Uttar Pradesh, India · Remote
01/03/2024 - 01/04/2024
Ahmedabad, Gujarat, India · Remote
10/03/2024 - 09/04/2024
Nashik, Maharashtra, India · Remote
15/03/2024 - 15/04/2024
Nashik, Maharashtra, India · Remote
15/03/2024 - 15/04/2024
Ahmedabad, Gujarat, India · Remote
17/03/2024 - 14/04/2024
Conducted a feasibility study using deep learning models for detecting anomalies in a cavitational desalination pump using unsupervised data.
Research Paper: Link
GitHub Repository: Link
Built a sentimental analysis model based on women's clothes e-commerce reviews.
Research Paper: Link
GitHub Repository: Link
Reviewed LSTM and GRU as a sequential recurrent network.
Research Paper: Link
Reviewed a study on different methods of Time Series Classification using neural networks.
Research Paper: Link
Built an automatic detector model on children toy cubes.
Research Paper: Link
GitHub Repository: Link
Conducted a study on LSTM and GRU in classifying and forecasting a time series dataset.
Research Paper: Link
GitHub Repository: Link
Conducted a data analysis of customer retention of a multinational chain of coffee houses.
Research Paper: Link
GitHub Repository: Link
Developed and designed a 2D topdown game called "The Code of Treasures".
Game Link: Link
Developed and designed a 3D game called "The Life of a Miner in Congo".
Game Link: Link
Conducted a Comprehensive Software Quality Assurance and Testing Initiative for www.asos.com
GitHub Repository: Link
This project aims to develop an automated plant disease classification system using machine learning and computer vision. The primary goal is to assist farmers in identifying diseases promptly, facilitating timely intervention and minimizing crop losses.
GitHub Repository: Link
This project involves creating a machine learning model for handwritten digit recognition using a dataset of pixel values and corresponding labels. The objective is to build and train an accurate model for classifying digits, with an extension to predict labels for an unlabeled test dataset.
GitHub Repository: Link
Explore team and player performance in the World Cup 2023 through comprehensive data analysis. Uncover patterns, trends, and key statistics to enhance understanding of cricket dynamics. Gain insights to inform strategic decisions for teams and players.
GitHub Repository: Link
Customer Churn Prediction project uses machine learning to forecast customer defection, helping businesses retain customers & minimize revenue loss.
GitHub Repository: Link
Email: hussainghonem99@gmail.com
Mobile no.: +20 1121332665
LinkedIn: Linkedin Profile
Moddb: Moddb Profile
ResearchGate: Research Gate Profile
GitHub: Github Profile