I am a fresh graduate specializing in data science. I graduated from the college of Artificial Intelligence at the Arab Academy for Science, Technology & Maritime Transport with knowledge in C/C++, Python, sorting/searching algorithms, Excel, Machine Learning, Deep Learning, NLP, Computer vision, SQL, MongoDB, Neo4j, and solid background in critical thinking and problem solving. I excel in cleaning data, conducting exploratory data analysis (EDA), engineering features, and building predictive models using machine learning algorithms. Moreover, I am capable of evaluating model performance, visualizing data to communicate insights, and deploying models into production.
As a graduate teaching assistant, I assist professors by delivering lectures, managing labs, and supporting students in AI courses. My role includes guiding lab exercises, providing feedback, and collaborating on instructional materials to effectively bridge theory with practice. Working as part of a dedicated team of TAs and professors, we actively pursue recognitions from esteemed organizations, representing our college in forming partnerships and securing sponsorships with regional institutions and organizations. Additionally, I supervise research projects undertaken by bachelor’s students alongside my teaching colleagues, and I engage in highly complex research initiatives with distinguished research pioneers throughout Alexandria, Egypt.
During my remote internship at that Indian startup, I collected and cleaned data, conducted exploratory analysis, engineered features, built and deployed machine learning models, created visualizations, and collaborated with teams while staying updated on data science trends.
During my internship, I specialized in performing dimensionality reduction with PCA, fine-tuning model parameters, and focused on backend development and model deployment, including creating the API. My team won Best Project Performance among four teams. I also participated with other team members in developing ML models, creating visualizations, and building an interactive web app using Flask to predict song popularity.
For a month, I worked on 4 projects that were going to be implemented using cutting-edge technologies in Computer vision and NLP such as Chatbot, real-time face mask detection, Boston houses pricing prediction and sign language classification.
Over three weeks, I used my skills in Python, matplotlib, seaborn, and statistics to handle customer sales data. I created storyboards, dashboards, PowerPoint slides, and documentation videos to record and present my progress.
for three weeks, I had been assigned multiple tasks and customer sales data generated from real world scenario using my solid background in programming and statistics to clean data and derive insights and notice all the trends and patterns within the real data.
I acquired skills in data analytics and cloud computing with Apache Spark and AWS, alongside a talented group of students and expert delegation from "Universitat Autònoma de Barcelona."
CV2, TensorFlow, PyTorch, Keras, Matplotlib, Numpy, Pandas
Tensorflow, OpenCV, SKlearn, Imutils, Numpy, Pandas
Python, Jupyter notebooks, Numpy, Pandas, NLP(NLTK), SKlearn
Python, Numpy, Pandas, Matplotlib, SKlearn, feature engineering, Exploratory Data Analysis
Python, Tensorflow, Keras, SKlearn, Numpy, Pandas, Seaborn
Python, PowerBI, Jupyter notebooks, Pandas and Seaborn
Linear Regression and Neural Networks algorithms
Python, Jupyter notebooks, Numpy, Pandas, Matplotlib, SKlearn
Python
HTML, CSS, Javascript, ejs, node js, SQL and MongoDB
Arduino
Our team won the 2023/2024 Computer Scientific Society Prize for Best Capstone Project, where we generated fraudulent Egyptian IDs using GANs, built an authentication system with CNNs and YOLO v8, and securely extracted and stored ID data.
My team and I were among 10 selected to present our research paper at the First International Conference for Universities and AI Technology in Amman, Jordan, attended by prominent figures including Dr. Amr Salama and Dr. Ismail Abdel Ghaffar.
While I was still bachelor student, I authored a Q2-ranked research paper introducing a novel approach using generative AI to enhance e-government services. We integrated OCR, developed a CNN achieving 99.5% accuracy for Arabic numbers recognition and improved fraud detection with SUGAN and StyleGAN2-ADA.
I helped set up and maintain the contest environment, managing servers, network infrastructure, and software tools. I provided technical support, ensured system stability, handled backups, and collaborated with organizers to meet technical requirements.
Present in a team of 4 students representing college of Artificial Intelligence in a TV program shown on AlShams channel called "Al-Sanai’aya"