Faculty of Data Science (FDS)

Action Slogan: "Leveraging technological foundations – Grounded in mathematical thinking – Mastering data – Pioneering intelligence – Advancing with UFM in the digital era!"

Dual Foundations (Prior to 2024):

The Faculty of Information Technology (established on May 27, 2004) pioneered academic training in Management Information Systems (MIS), bridging computing infrastructure with corporate administration. Simultaneously, the Department of Economic Mathematics served as an institutional pillar, cultivating quantitative modeling, advanced statistics, and analytical discipline for generations of students.

2024 – Strategic Consolidation:

The Faculty of Data Science was officially established through the merger of the Faculty of Information Technology and the Department of Economic Mathematics, marking a milestone repositioning designed to drive interdisciplinary education and high-impact digital transformation.

2025 – Launch of the Data Science Program:

The Faculty welcomed its inaugural cohort of undergraduate Data Science majors, focusing on end-to-end data lifecycle management, predictive analytics, and data-driven executive decision-making.

2026 – Launch of the Artificial Intelligence (AI) Program:

The Faculty initiated enrollment for the Artificial Intelligence program, completing an integrated academic ecosystem centered on machine learning, deep neural architectures, and autonomous intelligent systems.

1. Economic Mathematics

Inheriting the academic legacy of the Department of Economic Mathematics, this track serves as the methodological backbone for quantitative economic modeling, algorithmic design, and risk analysis across the university.

• Core Curricula: Mathematical Analysis, Linear Algebra, Probability & Mathematical Statistics, Optimization Techniques, Econometrics, and Quantitative Economic Modeling.
• Career Pathways: Quantitative Analysts (Quants), Financial Risk Analysts, Macro/Microeconomic Analysts, and Operations Research Specialists across commercial banks, investment funds, and securities firms.

2. Management Information Systems (MIS)

Building upon more than two decades of technological training, this discipline acts as a strategic interface linking IT engineering solutions with modern corporate management systems.

• Core Curricula: Database Architecture & Administration, Systems Analysis & Design, Enterprise Resource Planning (ERP), Information Security Management, and Digital Transformation Strategy.
• Career Pathways: Business Analysts (BA), IT Project Managers, ERP Implementation Consultants, and Digital Transformation Analysts.

3. Data Science

Launched in 2025, this program prepares professionals to master the full data lifecycle, extracting actionable business insights and delivering predictive models from complex, large-scale datasets.

• Core Curricula: Data Mining, Big Data Engineering, Predictive Modeling, Applied Machine Learning, and Enterprise Business Intelligence (Power BI/Tableau).
• Career Pathways: Data Scientists, Big Data Engineers, and Business Data Analysts across e-commerce platforms, retail enterprises, and digital financial institutions.

4. Artificial Intelligence (AI)

Inaugurated in 2026, this specialization represents the culmination of advanced computational mathematics and state-of-the-art machine learning, targeting next-generation automated systems.

• Core Curricula: Machine Learning, Deep Learning Architectures, Natural Language Processing (NLP), Computer Vision, Agentic AI Systems, and AI Ethics.
• Career Pathways: AI/ML Engineers, Intelligent Algorithm Developers, and AI Solutions Specialists focusing on enterprise workflow automation and financial technology (Fintech).

1. Rigorous Academic Grounding: Students master the mathematical principles governing modern algorithms rather than relying solely on pre-packaged software, ensuring long-term adaptability to rapid technological shifts.

2. Integrity and Data Governance: Strong emphasis is placed on social responsibility, algorithmic transparency, data privacy, and ethical standards throughout research and deployment.

3. Comprehensive Industry Engagement: Curricula are directly aligned with commercial demands through partnerships with financial institutions, commercial banks, and technology leaders, offering real-world capstone projects and internships.