Call for Applications: BSc in Data Science at UNIC Athens | Fall 2026

UNIC Athens announces the commencement of applications for the Bachelor of Science (BSc) in Data Science for the Fall 2026 academic semester. This programme is delivered on-campus and is taught in English.

School School of Sciences and Engineering
Department Computer Science 
Duration 4 years (8 semesters)
Number of Positions 60
Selection Criteria Under the Greek legal framework, applicants may be eligible to apply if they hold:

  • A General Lyceum (GEL) or Vocational Lyceum (EPAL) Leaving Certificate, with an average grade in the four (4) nationally examined subjects equal to or higher than the Minimum Entry Requirement, as determined per academic field for the year of examination.
  • An equivalent Secondary Education qualification issued by a recognized foreign school operating in Greece (Level 4 of the National Qualifications Framework).
  • An international or equivalent Secondary Education qualification obtained in Greece or abroad, granting eligibility for admission to higher education in the country of study.

Note: The above constitute the minimum legal eligibility requirements as defined by the applicable regulatory framework. Admission decisions are made by the University following a comparative evaluation of eligible applicants and are subject to the availability of places.

Regulatory Note: The provisions governing eligibility are defined by Greek law and may be subject to amendment. For secondary school graduates prior to the 2021–2022 academic year, as well as for applicants who already hold a recognized higher education degree, the selection and admission criteria of the University of Nicosia apply.
Application Deadline The application deadline for the Fall Semester is 31 August. Applications submitted after this date may be considered only subject to availability of places.
Start Date Fall 2026 Semester

Programme Overview:

The BSc in Data Science at the University of Nicosia is your launchpad into one of the world's most dynamic and in-demand fields. This program is designed to enable students to transform raw data into powerful insights that drive innovation across every industry. It equips students with foundational knowledge, essential technical skills, and problem-solving experience in AI, machine learning, big data, and programming for a data-driven world. By mastering these competencies, students will be prepared to solve complex real-world challenges and empower organizations through effective data-driven decision-making.

Programme Features:

  • Comprehensive foundation by integrating core principles from computer science, statistics, and mathematics to provide a robust understanding of the entire Data Science pipeline.
  • Prepares students for professional roles across AI and data-driven industries by emphasizing the integration of theory and cutting-edge technologies through projects, exercises, and laboratory work that use real data, simulators, and equipment (e.g., robots, drones).
  • Optional participation in trainings for industry certifications (e.g., Νvidia DL certification, AWS cloud academy certification, Google skill quests)
  • A dedicated industry placement component (internship as an optional elective course) that ensures students can apply obtained knowledge in a professional setting before graduating.

Unique and Innovative Curriculum:

  • Focus on AI and Machine Learning: The curriculum places a strong emphasis on the latest machine learning algorithms and artificial intelligence concepts, moving beyond basic analytics.
  • Big Data Technologies: Dedicated courses on handling massive datasets and AI models using modern frameworks and cloud computing, preparing for the scale of today's data challenges.
  • Ethical Data Handling and Governance: An integrated approach to the ethical and privacy implications of data collection and algorithmic bias, a critical skill for responsible Data Scientists.
  • Advanced Data Visualization and Communication: Learn to translate complex findings into compelling visual stories and actionable insights for business stakeholders.
  • Statistical Rigor for Business Intelligence: The curriculum emphasizes advanced statistical inference, enabling students to validate the correctness of their findings and communicate results with quantifiable confidence levels.
  • Modern Database Management: Training extends beyond traditional SQL to include NoSQL and Cloud databases, reflecting the diverse data storage needs of contemporary applications.
  • 3 Thematic Areas:
    Multi-Modal Artificial Intelligence
    Business Intelligence
    Data-Driven Internet Technologies

Admission Requirements: Admission Requirements – University of Nicosia

Further Information: https://www.unic.ac.cy/athens/data-science-bsc-4-years/