Institute of Graduate Studies and Research

Data Science (MSc)

Duration 2 Years
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About the Progeam

The Data Science Master's program at Cyprus International University, School of Applied Sciences, offers a comprehensive and in-depth education in data science and business analytics. The program focuses on providing students with advanced knowledge in data mining, machine learning, visualization techniques, predictive modeling, statistics, problem analysis, and decision-making. The program trains experts in statistical programming languages and big data tools and develops skilled professionals. These professionals can apply innovations in high-performance computing and conduct impactful research, contributing to the scientific community.

Education Opportunities

The Data Science Master's program is tailored to meet the growing demand for professionals and researchers in data management, big data, and data analytics. Students enrolled in the program will develop knowledge and skills in using a wide variety of tools, techniques, and methods for working with and conducting research on big data. The program offers a range of specializations, including Data Management, Data Mining and Statistical Analysis, Database Management, Machine Learning, Data Visualization, Business Intelligence, and Data Analytics. This diverse curriculum allows students to tailor their education to their specific interests and career goals.

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Career Areas

Graduates of the Data Science Master's program can expect strong job opportunities in a variety of sectors, as the demand for data scientists continues to outpace the supply. This favorable job market enables diverse career paths and opportunities for advancement in the field. Data science professionals can choose to specialize in a specific sector, such as marketing, or focus on a particular skill, such as machine learning. As they progress in their careers, data scientists have the option to take on leadership roles, managing teams and overseeing data-driven projects. Some of the many career possibilities for data science master's graduates include positions in data analysis, machine learning, big data management, data visualization, and business intelligence, among others.

Contact

Institute of Graduate Studies and Research
Graduate Sciences and Education Center, GE106
Tel: +90 392 671 1111 Extension: 2776
Institute E-mail: ciu-institute@ciu.edu.tr

Compulsory Courses

First Semester
RESEARCH METHODS

Course code

BASC501

Credit

3

Theoretical

3

Practical

0

Ects

This course introduces students to research methods and contemporary issues related to research in a university setting. Students will be introduced to research proposal development, scientific literature reviews, measurement analysis, statistical data analysis, and research planning techniques, good research practice, and oral and written research communication. Ethics and intellectual property topics related to research will also be covered. During this course, students will evaluate the broad impact of their engineering research and relevant constraints and data analysis skills. Also students will research, plan, execute and evaluate a self-defined research project. Research will focus on the Engineering Themes of Energy, Water, Health or Security.
DATA SCIENCE CONCEPTS AND PRACTICES

Course code

DASC501

Credit

3

Theoretical

3

Practical

0

Ects

8
The concepts of data science will be covered throughout the course from a variety of angles, including conceptual formulation and properties, solution algorithms and their applications, data visualization for exploratory data analysis, and the appropriate presentation of modeling outcomes. With the use of real-world examples, students will understand the purpose, effectiveness, and constraints of models. Upon completion of the course, students will be able to comprehend the contemporary data science landscape and technical terminology, identify key concepts and tools in the field of data science and determine when they can be applied effectively. Students will also be able to recognize the significance of curating, organizing, and wrangling data, explain uncertainty, causality, and data quality and anticipate the effects of data use and misconduct.
AREA ELECTIVE

Course code

DASC5X1

Credit

3

Theoretical

3

Practical

0

Ects

8
AREA ELECTIVE
AREA ELECTIVE

Course code

DASC5X2

Credit

3

Theoretical

3

Practical

0

Ects

8
AREA ELECTIVE
AREA ELECTIVE

Course code

DASC5X4

Credit

3

Theoretical

3

Practical

0

Ects

8
AREA ELECTIVE
Second Semester
SEMINAR

Course code

BASC590

Credit

0

Theoretical

0

Practical

0

Ects

Seminar course is designed to promote research interest in various areas of Electrical and Electronic Engineering. Students are expected to further advance and deepen their knowledge regarding research methods through discussions of research results made in their fields of specialization. Students will make presentations on the progress of their research and will hold discussions with teachers to expand the range of their research. An additional objective of the research seminars is to nurture global IT specialists by having students make presentations at national or international conferences. Students are required to attend both research seminars and conferences for developing their research ability. Master students must register and fulfill departmental requirements of the seminar.
ALGORITHMS FOR DATA SCIENCE

Course code

DASC502

Credit

3

Theoretical

3

Practical

0

Ects

8
This course covers the algorithmic techniques and approaches required to handle various types of structured, semi-structured and unstructured data. The goal of the course is to teach algorithmic methods that serve as the cornerstones for handling and analyzing large datasets in a variety of formats. The course specifically covers how to pre-process big datasets, store big datasets effectively, design quick algorithms for big datasets, and evaluate the performance of designed algorithms. Algorithms for sorting, searching and matching as well as graph and streaming algorithms will be introduced. Upon completion of this course, students will have a broad knowledge of different algorithms for pre-processing, organizing, manipulating and storing different data types. Students will also be able to carry out performance analysis of each algorithm.
AREA ELECTIVE

Course code

DASC5X3

Credit

3

Theoretical

3

Practical

0

Ects

8
AREA ELECTIVE
Third Semester
THESIS

Course code

DASC500

Credit

0

Theoretical

0

Practical

0

Ects

0
The aim of the thesis study is to develop the ability of the graduate students to search the literature on the thesis subject with the support of the thesis supervisor, to organize the information based on the literature, to use and develop the data collection tool, to collect the research data and analyze the data, to tabulate the research findings and to interpret the results from the research findings, to be able to draw conclusions, make suggestions, report the research and defend the research. At the end of the study, the graduate student is expected to present the thesis in front of the jury determined by the department.

Elective Courses

Students who are interested in pursuing advanced graduate studies leading to a master’s, doctoral degree, or professional doctorate degree for the Fall and Spring semesters every year. Applicants can directly apply online to our graduate programs using the application portal.

TRNC Applicants- Required documents:

  • Bachelor’s Degree Diploma
  • Bachelor’s Degree transcripts for each completed academic term/year.
  • Documents to prove English proficiency for English language departments,
  • Scanned copy of passport or identity card.

Click for detailed admission requirements information.

Students who are interested in pursuing advanced graduate studies leading to a master’s, doctoral degree, or professional doctorate degree for the Fall and Spring semesters every year. Applicants can directly apply online to our graduate programs using the application portal.

International Applicants- Required documents:

  • Bachelor’s Degree Diploma
  • Bachelor’s Degree transcripts for each completed academic term/year.
  • Evidence of English Language competence: TOEFL (65 IBT) or IELTS (5.5). Students without these documents will take the CIU English proficiency exam on campus following arrival.
  • Scanned copy of international passport/birth certificate
  • CV
  • Fully completed and signed CIU Rules and Regulations document (which can be downloaded during the online application)

Click for detailed admission requirements information.

Cyprus International University provides academic scholarships for its students as an incentive for success, with most students benefiting from 50%, 75% or 100% scholarships or discounted tuition fees. Click for more information.

Fee pe​r course     € 350,00
Fee for thesis     € 1.050,00
Fee for seminar     € 120,00 
Scientific Foundation per course     € 150,00
Annual Registration Fee € 295,00    
  VAT Exc.

*Applies to 1st. Year students. € 195,00 for others.