Ignacio Fernandez Fernandez

Program overview: A specialized postgraduate program combining artificial intelligence (AI), quantitative finance, and algorithmic trading. Designed in partnership with leading financial institutions, it provides both strong technical foundations and industry‑oriented application skills Key learning outcomes: - Advanced machine learning, predictive modeling, natural language processing, and risk management techniques tailored to financial decision‑making - Integration of quantitative analysis and automated trading systems for portfolio optimization and fraud detection - Use of industry tools and access to real‑world financial datasets, including BME’s proprietary market systems - Project‑based learning through case studies and collaboration with FinTech firms and financial institutions Competencies acquired: Technical: Building and validating AI models using Python, TensorFlow, Hugging Face, Scikit‑learn. Domain‑specific: Financial risk modeling, asset management, market microstructure. Soft skills: Multidisciplinary teamwork, critical thinking, communication, and regulatory/ethical awareness in financial AI

A four‑year (240 ECTS) undergraduate program specializing in software engineering, offered with a bilingual track that allows at least 120 ECTS credits—including core courses and final project—to be completed entirely in English. - Worked part time as an intern at the university of Oviedo - Acquired real-world software development team experience while completing academic studies with multiple internships. Final Year Project (TFG): Data quality Spark/Scala Solution for real client: Developed a production-grade Spark application in Scala based on a real Accenture project scoped for ENEL. Designed, implemented, and evaluated large-scale data processing pipelines, demonstrating strong technical and problem-solving skills in a professional context.