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The DS program combines theory and practice, based on three main disciplines, Computer Science, Statistics and Mathematics, and real-world application domains. It has been designed to enable graduates of the program to meet the demands of the data-driven economy of the future.
More specifically, the program aims at:
Providing students with the technical and analytical skills required for acquiring, managing, analyzing, and extracting insight from data.
Provide students with a strong mathematical and statistics foundation that will enable them to appropriately formulate models and apply optimization techniques for data analysis challenges.
Providing students with software engineering and machine learning skills to design and implement scalable, reliable, and maintainable solutions for data-oriented problems.
Enabling students to assess the level of privacy and security of a technical solution to a data science problem.
Preparing students to pursue further postgraduate education and research that require expertise in data science and analytical reasoning (such as business analytics, finance, health, bioinformatics).
Providing students with a strong sense of social commitment, global vision, and independent self-learning ability.
Learning Outcomes
Upon successful completion of this program, the students should be able to:
Apply theory and methodologies of several data science-oriented topics in mathematics, statistics, and computing to solve problems in real-world contexts.
Apply contemporary computing technologies, such as machine learning and data mining, Artificial Intelligence, parallel and distributed computing, to solve practical problems characterized by big data.
Implement algorithms for fundamental data science tasks such as machine learning and data mining, statistical inference, etc, using a high-level language that is suitable for data science (e.g. Python, R).
Apply data management to clean, transform and query data.
Select and apply suitable machine learning algorithms and software tools to perform data analysis.
Perform data visualization and apply inference procedures to analyze data and interpret and communicate results.
Assess the data privacy and security issues raised during the various stages of data management.
Demonstrate professional and ethical responsibility in data ownership, security, and sensitivity of data.
Be able to communicate technical ideas effectively through both oral presentations and written reports.
Entry Requirement
Academic Requirements:
The minimum admission requirement to the programme of study is a recognized High School Leaving Certificate (HSLC). Students with a lower HSLC grade than 7.5/10 or 15/20 or equivalent depending on the grading system of the country issuing the HSLC are provided with extra academic guidance and monitoring during the first year of their studies.
Graduation Requirements:
The student must complete 240 ECTS and all programme requirements.
A minimum cumulative grade point average (CPA) of 2.0 is required. Thus, although a ‘D-‘ is a PASS grade, in order to achieve a CPA of 2.0 an average grade of ‘C’ is required.
English Language Requirements:
The list below provides the minimum English Language Requirements (ELR) for enrollment to the programme of study. Students who do not possess any of the qualifications or stipulated grades listed below and hold IELTS with 4.5 and above, are required to take UNIC’s NEPTON English Placement Test (with no charge) and will receive English Language support classes, if and as needed, from UNIC’s International Gateway Centre (IGC).
TOEFL – 525 and above
Computer-based TOEFL – 193 and above
Internet-based TOEFL – 80 and above
IELTS – 6 and above
Cambridge Exams [First Certificate] – B and above
Cambridge Exams [Proficiency Certificate – C and above
GCSE English Language “O” Level – C and above
Michigan Examination of Proficiency in English (CaMLA) – Pass
Pearson PTE General – Level 3 and above
KPG (The Greek Foreign Language Examinations for the State Certificate of Language Proficiency) – Level B2 and above
Anglia – Level B2 and above
IEB Advances Programme English – Pass
Examination for the Certificate of Proficiency in English (ECPE) Michigan Language Assessment by: Cambridge Assessment English & University of Michigan – 650 average score for ALL skills and above.
Fees
Yearly Tuition (for 60 ECTS): € 9420
This information was accurate on : 21/01/2021 Please contact us for more information about this courses
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