Undergraduate

Data Analytics

General Information

The Data Analytics program is an interdisciplinary field that prepares specialists in collecting, processing, analyzing, and interpreting large volumes of data. The program integrates mathematics, statistics, programming, artificial intelligence, and business analytics to equip students with data-driven decision-making skills.

In today’s world, organizations make strategic decisions based not on intuition but on data-driven approaches. This program is designed to prepare professionals capable of supporting such decisions.

Program Learning Outcomes (PLOs)

Upon successful completion of the Data Analytics program, graduates will be able to:

• Apply principles of mathematics, probability theory, and statistics to analyze, interpret, and model data-driven problems.
• Design, implement, and optimize data processing solutions using modern programming languages (e.g., Python, R) and data analytics tools.
• Collect, clean, transform, store, and manage structured and unstructured data using database systems and data engineering techniques.
• Apply appropriate analytical, statistical, and machine learning methods to extract meaningful patterns, trends, and insights from data.
• Develop, evaluate, and interpret predictive and prescriptive models using machine learning and AI techniques.
• Effectively communicate analytical results through professional reports, dashboards, and visualizations tailored to technical and non-technical audiences.
• Formulate real-world problems into data-driven analytical frameworks and propose evidence-based solutions.
• Apply ethical principles, data privacy regulations, and professional standards in handling and analyzing data.
• Work effectively in multidisciplinary teams and manage data analytics projects using appropriate methodologies.
• Engage in independent learning, research activities, and continuous professional development in emerging data analytics technologies.