AI Engineer with less than a year in Data Science & AI
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Motivated engineering student specializing in Data Science, Big Data, and Artificial Intelligence, currently seeking an internship opportunity. Skilled in Python for data analysis, visualization, and machine learning, with hands-on experience using libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib. Familiar with, NLP, Generative AI, LLMS, and RAG systems through projects. Fast learner, problem solver, and eager to contribute to innovative real-world projects.
ENSA Agadir (National School of Applied Sciences)
Engineering Cycle · Data Science, Big Data & AI
August 1, 2025 – Present
ENSA Safi (National School of Applied Sciences)
Preparatory Cycle
August 1, 2023 – June 30, 2025
Al Tabari High School
Baccalaureate · Physical Sciences
N/A – May 31, 2023
ENSA Agadir
Logistics Team Member (Staff) – Info Days 2.0
April 24, 2026 – April 26, 2026
Agadir, Souss-Massa, Morocco
AI Cybersecurity Chatbot using ML, RAG & LLM
June 1, 2026 – Present
Built an AI-powered cybersecurity chatbot for intrusion detection and attack explanation. Trained a machine learning model on network traffic data to detect malicious activities. Implemented RAG with a vector database to retrieve cybersecurity knowledge efficiently. Integrated an LLM to generate contextual explanations and security recommendations.
Customer Churn Prediction
June 1, 2026 – Present
Built a machine learning model to predict customer churn using the Telco Customer Churn dataset. Performed data cleaning, preprocessing, and EDA to identify churn patterns. Implemented and compared multiple models: Logistic Regression, Random Forest, and Gradient Boosting. Evaluated models using recall, F1-score, and feature importance to improve performance.
Initiation à l'IA Embarqué Avec Raspberry Pi
Orange Digital Center Agadir
April 1, 2026 – Present
Python for Data Science
IBM
January 1, 2026 – Present
Git and GitHub
365 Data Science
November 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative and a proactive approach to learning and applying AI/ML concepts. The participation in organizing a tech event (Info Days 2.0) indicates a willingness to contribute to a community and work in a team, suggesting a positive cultural fit for collaborative environments. The diversity of projects (cybersecurity, customer churn) shows a breadth of interest within AI/ML. However, the experience is primarily academic, and exposure to diverse professional work cultures is limited.
Soft Skills & Operational Fit
The candidate's experience as a Logistics Team Member suggests organizational skills, teamwork under pressure, and event coordination abilities. These indicate a capacity for operational tasks and collaboration, which are valuable in a professional setting. However, direct evidence of problem-solving or critical thinking in a technical context is limited to project descriptions.