Mounia BADDOU

AI Intern @ Développement & intégration ERP métier | Transformation digitale | Partenaire agréé Sage Maroc

About

👋 Hi, I'm Mounia, a passionate Computer Science undergraduate at UM6P's College of Computing with a strong foundation in machine learning and cybersecurity. 🔍 My interests span NLP and AI-driven security solutions, and I enjoy learning about complex problems that bridge these domains. I'm currently working on projects involving predictive modeling for renewable energy, blockchain systems in C++, and secure authentication mechanisms in Go. 💡 I have experience working with Python, Java, C++, Go, PostgreSQL, and modern frontend frameworks like VueJS and Tailwind. 🕵️‍♀️ I also have a deep curiosity about the history of cyberattacks and how cybersecurity strategies have evolved over time. Understanding past security breaches helps me better understand the development of malware and how historically solutions were found. 🚀 Always eager to learn and contribute, I'm actively looking for AI/ML and cybersecurity opportunities where I can apply my skills while growing alongside inspiring teams. 📬 Let’s connect and discuss how AI and security can shape the future!

Country

Morocco

City

Marrakesh

Industry

Skill

Data Analysis, Automation, Large Language Models (LLM), Microsoft SQL Server, n8n, Go (Programming Language), Java, SQL, Project Management, C (Programming Language), Linux, RISC-V, Python (Programming Language), Network Services, IT Networking, Network Installation, Computer Assistance

Experience

AI Intern

Développement & intégration ERP métier | Transformation digitale | Partenaire agréé Sage Maroc

2025-6 - 2025-8 · 3 mos

Agadir, Souss-Massa, Morocco

Designed and implemented a secure AI-driven data analytics system for industrial databases, aimed at democratizing access to sensitive business data for non-technical users. Key contributions: - Built an automated Text-to-SQL analytics pipeline enabling natural-language queries over large-scale Microsoft SQL Server databases (millions of records). - Led an iterative R&D process (PoC → production-like architecture), evaluating RAG-based approaches vs. direct SQL generation for performance and scalability. - Architected a modular Python + n8n workflow separating query execution, security, AI analysis, and result rendering. - Implemented data obfuscation / lightweight encryption mechanisms to protect sensitive textual fields before AI processing. - Integrated LLM-based analysis and report generation, producing KPIs, trends, and actionable insights. - Contributed to a chatbot + KPI dashboard enabling non-SQL users to interact safely with enterprise data.