School of Applied Sciences

Data Science

Duration 4 Years
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About the Program

During the IT boom of the late 1990s and early 2000s, the focus was on the shift of offline business processes to automated computer systems. During these two decades there have been consistent streams of electronic content creation, transactional data generation, and data logs. This means that every organization is now sitting on a pile of data that they know can have rich value. From healthcare to politics to disaster management, data science is driving breakthroughs everywhere. Data helps businesses understand and improve their business processes, saving time and money. The aim of this program is to provide students with technical skills and practical knowledge in Data Science. The Data Science program combines theory and practice and is based on three major disciplines, Computer Science, Statistics and Mathematics, and real-world application areas. This program is designed to enable graduates to meet the demands of the data-driven economy of the future.

Education Opportunities

Students graduating from the Data Science program will develop relevant programming skills, demonstrate proficiency with statistical analysis of data, develop the ability to build and evaluate data-driven models, perform statistical analysis with professional statistical software, demonstrate skills in data management, and use data science concepts and methods to solve problems in real-world contexts and effectively communicate these solutions. The goal of the program is to provide students with the technical and analytical skills necessary to manage, analyze and make sense of data, and to equip them with the knowledge and skills necessary to take on innovative roles. The program will contribute to the gap in both the public and private sectors by training experts with up-to-date knowledge in the field of data science.

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Career Areas

Data science-related careers are expected to have strong job opportunities. That means there is a greater demand for data scientists than there is supply, which is fantastic news for students and professionals in the field. As a result of this scarcity, you'll discover that a data science profession can take many different directions. A position in data science offers a variety of career possibilities in addition to being one of the most paid tech occupations. As data scientists advance in their careers, their options become increasingly numerous, and many senior data scientists are given with the decision of where they want to specialize. Some data scientists aspire to lead teams. Others opt to concentrate in a single field, such as marketing, or to focus on a specific skill, such as machine learning.

Contact

School of Applied Sciences
Science and Technology Center, ST256
Tel: +90 392 671 1111 Extension: 2751
School E-mail: secretary-sas@ciu.edu.tr
Director: Assoc. Prof. Dr. Müesser NAT
Director E-mail: mnat@ciu.edu.tr

Compulsory modules

First Semester
INTRODUCTION TO BUSINESS-I

Course code

BUSN101

Credit

3

Theoretical

3

Practical

0

Ects

6
This course is designed to teach introductory business students fundamental knowledge about a business. For this purpose, understanding the contemporary business environment is a starting point. After briefly covering the business of managing, all functional areas of a business are discussed. Upon completion, students should be able to demonstrate an understanding of business concepts as a foundation for studying other business subjects. The students will be able to identify potential marketing opportunities, relate how business institutions are operated nowadays, and describe business ownership forms. The course is also designed to expose students to the multitude of career fields in the area of business and it will also help them to obtain information about starting their own businesses, identifying basic long and short term planning techniques.
MICROECONOMICS

Course code

ECON101

Credit

3

Theoretical

3

Practical

0

Ects

7
This course involves introduction to economics with the question; What is economics? Micro and Macro Economics, Needs, wants, preferences, scarcity and consumer preferences, Production Possibilities Frontier, Opportunity Cost, Budget Line, Cost-Benefit Principle, Explicit and Implicit costs, Elasticity -Inferior goods, normal goods, luxury goods, complement goods and substitute goods, Demand Curve and Supply Curve, Excess demand and supply, Demand and Supply functions, Equilibrium price and quantity by using functions, Types of taxes and their effects on demand and supply,Types of Costs; Fixed costs and variable costs. Calculating total revenue and total costs, Calculating profit and loss, Calculating Break even quantity, Drawing Break Even chart, Types of Depreciation and calculating depreciation all will be focused on.
READING AND WRITING SKILLS-I

Course code

ENGL141

Credit

3

Theoretical

2

Practical

2

Ects

4
This course aims to develop students' listening, speaking, reading - writing and study skills. The course provides students with the opportunity to develop their communication skills through controlled activities and to equip students with the basic study skills necessary to follow the curriculum of English. This course also provides students with the opportunity to process the newly acquired knowledge and to develop their ability to ask questions about how to apply the new knowledge to new situations and ask them to think critically. In addition, this course will enable students to learn about the different strategies required to review the various reading pieces, such as finding the main idea and distinguishing the details from the main idea.
FUNDAMENTALS OF COMPUTING

Course code

ITEC103

Credit

3

Theoretical

2

Practical

0

Ects

0
This course serves as an introduction to the basic component of information systems, hardware, software, data, people and networks. Topics covered includes computer networks and communications, systems and application software, computer hardware and its operation, the internet and the world wide web, algorithms, pseudocodes and flowchart. After the completion of the course, students will be able to differentiate between various operating systems and application programs. They will be able to identify computer tools that can be used to assist with various common computer applications. They will also gain the fundamental understanding of the history and operation of computers, programming, and web design.
CALCULUS-I

Course code

MATH101

Credit

4

Theoretical

3

Practical

2

Ects

5
Calculus-I provides the methods of differential and integral calculus with applications in geometry, physics and engineering. Students in this course will learn how to use mathematical language needed for applying the concepts of calculus to numerous applications in science and engineering such as identifying types of functions, graph of functions, evaluating limit of functions, limit of elementary functions (polynomial, trigonometric, logarithmic, exponential,…), methods to solve the undefined limits (L’Hopitals Rule), continuous functions, evaluate derivative of functions, definition of derivative, derivative of elementary functions, derivative of product of two functions and division of functions, applications of derivative, evaluate integrals of functions, definition of the integral, integral of elementary functions, substitution method, integration by parts, integral of rational functions, application of the integral (finding the area) .
TURKISH LANGUAGE

Course code

TREG100

Credit

0

Theoretical

2

Practical

0

Ects

2
The aim of the course is to develop language consciousness, to improve the grammatical knowledge, and to increase the understanding and writing skills. This course is based on the educational development of the usage of the language and improvement of expressions. Improvement of basic knowledge about the Turkish language is the main target.
TURKISH

Course code

TURK100

Credit

0

Theoretical

2

Practical

0

Ects

2
This course provides an orientation to modern Turkish language for foreign students who wish to communicate in this language for their needs. It mainly focuses on the differences between Turkish and English Alphabets, especially the sounds and the letters which are not included in the English alphabet (i.e. Turkish letters ç-ğ-i-ö-ş-ü). In addition, basic grammar and sentence structure forms in Turkish are practised. The required grammar and vocabulary will also be developed through their adaptation to daily situations in contexts such as introducing yourselves, greeting, talking about the things they possess by using possessive adjectives, forming positive, negative and question sentences by using present simple, telling the time, talking about their own timetables, using demonstrative pronouns when describing the place of objects and becoming familiar with vocabulary related to family members.
Second Semester
READING AND WRITING SKILLS-II

Course code

ENGL142

Credit

3

Theoretical

2

Practical

2

Ects

4
This course is the continuation of ENG 101. The course aims to improve students' listening, speaking, reading, writing and working skills. In the course, students are guided in writing compare and contrast essays using Venn diagram. In addition, the aim of the course is to learn the necessary conjunctions for composition writing. In addition, the students will be able to write a four-part critical composition by learning the difference between ideas and factual real sentences and how to write the opposing opinion and sentences used to refute it. Thus, the students will be able to distinguish between the compare and contrast essay and discursive essay. Students will also be able to make presentations by using presentation techniques. In addition, this course aims to summarize the reading pieces of the students and to use the strategies of reading and to draw conclusions and meanings using their reading skills.
HISTORY OF CIVILIZATION

Course code

HIST100

Credit

0

Theoretical

2

Practical

0

Ects

2
The aim of this course is to outline the development of civilizations in the course of history. It firstly focuses on the concepts such as “Civilization”, “Prehistoric”, and “Historic” and on the factors forcing the emergence of the first civilizations. As well as examining the prehistoric periods and their characteristics in the course of human life since the first appearance of human beings on earth, the course mainly focuses on the early civilizations, namely the Mesopotamian, Egyptian, Aegean, Classical Greek, Hellenistic, Indian, Chinese and Roman Civilizations. Political, social, economical, cultural, intellectual, philosophical and scientific aspects in these entities are also examined in this course.
FOUNDATIONS OF INFORMATION TECHNOLOGY

Course code

ITEC104

Credit

3

Theoretical

3

Practical

0

Ects

6
This course is designed to introduce students to contemporary information systems and demonstrate how these systems are used throughout global organizations. The focus of this course will be on the key components of information systems - people, software, hardware, data, and communication technologies, and how these components can be integrated and managed to create competitive advantage. The necessary topics that will be covered in this course are; how and why information systems are used today, how organizations are using information systems for competitive advantage vs. competitive necessity, information technology concepts such as hardware and software, telecommunication and networks, internet, intranet, extranet, electronic and mobile commerce, enterprise systems, decision support systems and knowledge management.
INTRODUCTION TO PROGRAMMING

Course code

ITEC112

Credit

4

Theoretical

3

Practical

2

Ects

6
The course will introduce basic and fundamental programming constructs and techniques through using the C++ programming language in order to generate algorithmic solutions to problems. Upon completion of the course, students will learn an introduction to algorithms, solving problems by flowcharts and pseudo codes, header files, data types, arithmetic & logic operators, control statements (if, if/else, switch-case) and use them as inner statements, loop statements (while, do/while, for), functions, standard functions of programming language, random number generation and their area of use, user-defined functions, global and local variables, recursion, arrays, searching algorithms on arrays, sorting algorithms on arrays, pointers, pointer operators, using pointers with arrays and functions. In the laboratory hours, students are writing full programs or modifying existing programs for other solutions.
DISCRETE MATHEMATICS

Course code

MATH122

Credit

3

Theoretical

3

Practical

1

Ects

4
The objective of the course is to introduce the students fundamental principles: logic and Boolean algebra, set theory, relations( Partial ordering, Total ordering and Hasse diagrams, Equivalence relations and equivalence classes), functions(one-to-one, onto, identity, inverse and composition of functions), inductive proofs and recurrence relations, counting techniques(multiplication and addition rules, permutations, combinations, unordered samples with repetitions, principle of inclusion and exclusion, pigeonhole principle) and introduction to graph theory(basic terminology like vertex, edge, degree of a vertex in directed and undirected graphs, Eulerian and Hamiltonian graphs, trees and spanning trees, minimal spanning trees, Prim’s Algorithm, Kruskal Algorithms, Shortest Path Problems, Dijkstra’s Algorithm).
MODERN TURKISH HISTORY

Course code

TARH100

Credit

0

Theoretical

2

Practical

0

Ects

2
In this course, Ottoman state and society, factors causing the collapse of the state; Ottoman modernization; Tripoli and Balkan Wars, World War I, Mudros Armistice and Sevres Agreement; parties and associations, the national resistance movement led by Mustafa Kemal, the Havza and Amasya Circulars, the Congresses, the National Pact, the Turkish Grand National Assembly; the rebellions, the regular army and the War of Independence; the Mudanya Armistice, the Lausanne Peace Treaty; Revolution in the political field, secularization of the state and society, abolition of the sultanate, declaration of the republic, abolition of the caliphate; 1921 and 1924 constitutions, constitutional changes; Sheikh Said Rebellion; Multi-party experience, secularization and modernization in law, nationalization and secularization in education, Kemalizm and 6 principles, Turkish foreign policy(1923-1938) are covered.
Third Semester
FUNDAMENTALS OF DATA SCIENCE

Course code

DASC201

Credit

3

Theoretical

3

Practical

0

Ects

6
This course focuses on learning data science through the interest to development and improvement of capability of solving rich problems from data point of view in a systematic and principled way by using high quality instructions and basic level data science techniques. Students will be introduced to what data science is, will discover the applicability of data science across fields, and will learn how data analysis can help them make data driven decisions. Students will gain familiarity with various open source tools and data science programs used by data scientists, like Jupyter Notebooks, RStudio, GitHub, and SQL. This course provides the students with the required structure and responsibilities in order to educate them as data scientists progressing a right way with high concluding capabilities.
INTERNET TECHNOLOGIES

Course code

DASC283

Credit

4

Theoretical

3

Practical

2

Ects

7
This course looks into internet and global network concepts are taken up in detail. This course also deals with the most popular topics such as the history of Internet, a general overview of the internet based opportunities and applications (such as e-mail, internet browsers, file transfer opportunities, list drivers, etc.) internet based research and information resources, the global network services, creation of web pages using HTML. A history of the technologies appeared upon development of internet and an overview of the mentioned technologies together with the methods of utilization of these technologies for personal and business purposes is provided to the students.
ALGORITHMS AND PROGRAMMING

Course code

ITEC223

Credit

4

Theoretical

3

Practical

2

Ects

6
The course mainly focuses on software implementations in C Programming Language. Firstly, basic concepts of algorithms are discussed and then structures of programming are studied. Then, arrays and searching and sorting algorithms on arrays are studied. Fundamentals of basic data structures, which are arrays, structures and unions are discussed together with bitwise operations and enumerations in C. Pointers, functions and file processing are studied in the second part of the course, after midterm examination. Case studies related to searching and sorting algorithms are also studied. Functions, characters and strings are studied as last topics of algorithm developments and course is finalized with complexity analysis of algorithms.
LINEAR ALGEBRA

Course code

MATH121

Credit

2

Theoretical

2

Practical

0

Ects

3
The aim of this course is to introduce the basic operations in linear algebra and applications in engineering problems; matrices, matrix properties and matrix operations: Addition, scalar multiplication, multiplication, transpose, solution of system of linear equations: Elimination method, Gauss Jordan forms, inverse method to solve linear systems, row reduced echelon forms, Gaussian elimination method, inverse and determinants: solving linear equations with determinant (Cramer's rule), use one row to evaluate determinant, minor, cofactor, adjoint matrix, identity matrix, square matrix of the matrices. Real vector spaces, vectors and their properties and applications in engineering: Addition, subtractions, dot product, scalar multiplication, cross product, basis, dimensions and subspaces.
INTRODUCTION TO PROBABILITY AND STATISTICS

Course code

MATH205

Credit

4

Theoretical

4

Practical

1

Ects

5
The objective of this course is to introduce basic probability concepts and basic statistics. The focus of this course is on both applications and theory. Topics include: introduction to random variables, simple data analysis and descriptive statistics, frequency distribution, cumulative distribution, sample space, events, counting sample points (basic combinatorics), probability of an event, probability axioms, laws of probability, conditional probability, Bayes’ rule, discrete and continuous random variables, probability distributions, cumulative probability distributions, discrete and continuous probability distributions, discrete uniform, Binomial, Geometric, Hypergeometric, Poisson, Continuous uniform, Normal Disributions, Gamma and Exponential distribution, jointly distributed random variables, expectation and covariance of discrete and continuous random variables, random sampling, sampling distributions, distribution of Sample Mean, Central Limit Theorem(CLT).
Fourth Semester
FOUNDATIONS OF RESEARCH METHODS

Course code

APSC220

Credit

3

Theoretical

3

Practical

0

Ects

0
Research Methods is an introductory course in information technology. It aims to introduce the student with the basic concepts and problems encountered in an IT and social scientific investigation. Research methods objective is to explain the main concepts related to the methodology of conducting research in IT. Also it explains the importance and limitations of theory and methodology in IT research as well as the purposes of applied research evaluation, analysis techniques, and research ethics. Moreover, the course introduces the field of scientific methodologies by providing basic research techniques and tools to the students. Also, the procedures for writing research papers and reports, literature review for journals and books and doing practical research are introduced
DATA VISUALIZATION

Course code

DASC202

Credit

3

Theoretical

3

Practical

1

Ects

6
This course provides a comprehensive understanding of transforming data into visuals by introducing participants to important principles of analytical design and practical data visualization techniques for the exploration and presentation of univariate and multivariate data. Data visualization is covered as one of the most effective tools to explore, understand, and communicate patterns in quantitative information. The course provides a broad understanding of techniques and algorithms of turning data into readable visuals. Upon completion of the course, students learn about data visualization processes including data modeling, data aggregation and filtering, mapping data attributes to graphical attributes, and visual encoding. Students also learn to assess the effectiveness of different visualization designs, and critically evaluate each design decision.
VISUAL PROGRAMMING

Course code

ITEC214

Credit

3

Theoretical

3

Practical

1

Ects

6
This course is an introductory programming course for visual programming. Event-driven, visual and structured programming concepts will be presented. Initially, the emphasis will be on fundamentals of visual programming and basic controls. Then, advanced controls, file and database management features will be presented. Programming projects will involve common problems that require data entry, display of calculated results, conditional testing, arithmetic operations, array processing, searching, sorting, reading and writing files, and operations on databases.
DATA STRUCTURES AND DATA ORGANIZATION

Course code

ITEC242

Credit

4

Theoretical

3

Practical

2

Ects

6
The objective of this course is to provide the basics of data structures and data organization. The course will introduce C/C++ and algorithms for the implementation of data structures which are stack, queue, linked list, tree. Also, the applications of data structures covering stack applications which are paranthesis checker, infix to postfix and prefix conversions, recursion, dynamic stack and queue, tree traversals. Linked lists with their types and implementations are also studied in details. Theoretical aspects of most widely used data structures will be covered during the lectures. Programming assignments and labworks cover the C/C++ implementations of applications of data structures that are discussed in the lectures.
Fifth Semester
STATISTICAL MACHINE LEARNING

Course code

DASC311

Credit

4

Theoretical

3

Practical

2

Ects

7
In this course, statistical machine learning which has roots in computer science, artificial intelligence and statistics is covered and a broad understanding of algorithms that allow computers to improve their performance through the process of ‘learning’ and enable them to make decisions and predictions is provided. Fundamental methods are taught and applied to real data. The term statistical in title emphasizes the statistical techniques, which form dominant approaches to machine learning. The course integrates methodology with theoretical underpinnings, computational elements, and statistical theory issues. By completion of this course, students are expected to learn about supervised and unsupervised learning approaches to speech recognition, internet search, bioinformatics, image and audio signal analysis, data mining and exploratory data analysis.
APPLIED ARTIFICIAL INTELLIGENCE

Course code

DASC317

Credit

3

Theoretical

3

Practical

0

Ects

5
In this course Artificial Intelligence (AI), which is a discipline of computer science concerned with the development of intelligent machines capable of executing difficult tasks that would otherwise necessitate human intervention and intelligence is covered. Students will learn about how Artificial intelligence uses real-world data to allow machines and computers to mimic the human mind's decision-making and problem-solving abilities. Students will also learn about AI tools and applications that are using huge amounts of data from novel sources. The topics covered are AI methodology and fundamentals, intelligent agents, supervised and unsupervised learning, decision tree learning, neural networks, support vector machines, statistical learning and fuzzy logic. Upon the completion of this course, students will be familiar with the basic principles, techniques and real-world applications of AI.
PRINCIPLES OF DATA MINING

Course code

DASC325

Credit

4

Theoretical

3

Practical

2

Ects

7
Data mining, which is the study of algorithms and computational paradigms that enable computers to search datasets for patterns and regularities and make predictions and forecasts is covered in this course. Knowledge discovery is introduced comprehensively. The course explores data selection, cleaning, coding, the application of various statistical and machine learning approaches, and visualization of the resulting structures, which are all steps in knowledge discovery. Students who successfully complete this course are supposed to learn about several data mining techniques, including classification, rule-based learning, decision trees, and association rules. Additionally, students are expected to learn about selection and cleaning of data, machine learning methods for "learning" about "hidden" patterns in data, and reporting and visualizing the resulting knowledge.
AREA ELECTIVE

Course code

DASCXX1

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE
DATABASE MANAGEMENT SYSTEMS I

Course code

ITEC343

Credit

4

Theoretical

3

Practical

2

Ects

7
At the end of this course, students are expected to have experience and knowledge on databases, database design and SQL. Introduction to DBMS (Definition, characteristics, levels of abstraction, advantages, query types), Relational database (relational model, database design), Relational Algebra, SQL, Data Manipulation Language (DML), nested queries, sub-queries, joins, grouping, row functions, aggregate functions, Data Definition Languages (DDL) with constraints like primary key, foreign key and case constraints will be covered. Also, database user management and user rights will be explained.
Sixth Semester
BIG DATA CONCEPTS AND APPLICATIONS

Course code

DASC336

Credit

0

Theoretical

3

Practical

0

Ects

7
This course covers big data, which becomes increasingly available with digitalization of many aspects of human life and with increasingly growth of social media platforms. The course presents a broad understanding of big data and different approaches of big data manipulation. Students will explore how terabytes and petabytes of storage space can be occupied by big data. In this course, the Hadoop software, the Hadoop Distributed File System (HDFS) and the MapReduce technique as well as supervised and unsupervised machine-learning approaches are introduced and artificial neural networks are thoroughly investigated. By completion of the course, students are expected to be able to harvest big data sets from the internet and process by using different methods and tools.
FORECASTING ANALYSIS

Course code

DASC348

Credit

4

Theoretical

3

Practical

2

Ects

7
This course covers the fundamentals of data analysis with the aim of prediction which is also called predictive analytics. Traditional statistical methods related to prediction, linear regression analysis, logistic regression analysis, clustering, factor analysis and time series are covered in a comprehensive way. Precedent, practical case studies with the aim of examining the application of regression analyzes to real-world business intelligence use cases are examined. Students explore the descriptive machine learning tools and techniques that use diagnostic measures such as R-Square, Mean Error, F-Significance, and P-Values to describe model quality. Students will internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.
AREA ELECTIVE

Course code

DASCXX2

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE
DATABASE MANAGEMENT SYSTEMS II

Course code

ITEC344

Credit

4

Theoretical

3

Practical

2

Ects

6
Fundamental concepts and applications about DB architectures will be discussed like properties of popular databases, backup, recovery, replication and reverse engineering. Also, students will gain knowledge on transactions, indexes, PL/SQL, Triggers, stored, functions, stored procedures and cursors. Views, materialized views, query performance optimization, database application Development with a programming language and SQL injection will also explained. Case studies will cover the topics studies in this lecture.
UNIVERSITY ELECTIVE

Course code

UNIEXX1

Credit

3

Theoretical

3

Practical

0

Ects

4
UNIVERSITY ELECTIVE
Seventh Semester
SUMMER TRAINING

Course code

DASC300

Credit

0

Theoretical

0

Practical

0

Ects

5
Summer Training is a great opportunity that gives students practical, real-world experience in a working environment. Students are expected to complete their industrial training by spending at least thirty working days to gain practical experience. They will gain experience in a field of interest. Among the fields they can choose to study are web design and/or content management systems, project management, software development, cloud management, database management systems, embedded systems and business intelligence. At the end of this training, each student is obliged to submit a report of all the activities that took place in their summer training. In this report, students are asked to include what they learned, the mistakes they made, and the difficulties they encountered while participating in this training.
PROJECT MANAGEMENT

Course code

DASC401

Credit

3

Theoretical

3

Practical

1

Ects

4
The aim of this course is to provide students with a broad knowledge of the processes and management practices related to a project management profession. This course is only offered to students who will take their graduation project in the next semester. Students are taught basic project management procedures and various project management tools are introduced. At the end of this course, the student is given a multi-disciplinary project topic and they are provided to work as a team with the students of other departments. A feasibility study is made and the study is presented to the students' advisors. At the end of the evaluation, the project in question is accepted as a graduation project.
AREA ELECTIVE

Course code

DASCXX3

Credit

3

Theoretical

3

Practical

-3

Ects

5
AREA ELECTIVE
AREA ELECTIVE

Course code

DASCXX4

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE
DATA AND NETWORK SECURITY

Course code

ITSE479

Credit

3

Theoretical

3

Practical

0

Ects

0
This course discusses different types of malicious attacks and various methods of mitigating to them. Students learn how to protect computer networks by using security codes. Topics covered includes foundations of network security, IP packet structure and analysis control, routing and access control lists, attack techniques, network defense fundamentals, sign-on solutions and file encryption solutions. At the end, the course students will be able to understand the security problems introduced by the combination of the Internet with Intranets, mobile devices, and sensors networks. Students will also be able to develop a basic understanding of the theoretical and conceptual aspects that are needed to build secure systems.
UNIVERSITY ELECTIVE

Course code

UNIEXX2

Credit

3

Theoretical

3

Practical

0

Ects

4
UNIVERSITY ELECTIVE
Eighth Semester
DATA SCIENCE PROJECT

Course code

DASC402

Credit

4

Theoretical

2

Practical

4

Ects

8
As a continuation of project management course students are expected to complete the structure of the project they started in DASC401, with limited supervision as an independent study. During the project, students should complete the feasibility study by explaining the aims, objectives, tasks, milestones, duration and development of the project. At the end of the project, students will also have information about the subjects of other departments. This way, the student will be able to associate his field of specialization with the subjects of other departments. Upon completion of the project, the student is required to submit a project report and conduct an oral presentation.
DATA PRIVACY AND ETHICS

Course code

DASC482

Credit

3

Theoretical

3

Practical

0

Ects

7
This course explores the many ethical dilemmas that arise in the contemporary practice of data science and creates a framework for comprehending these concerns. The impact of unethical behavior and how data are used ethically in society will be covered. The Findable, Accessible, Interoperable, and Reusable (FAIR) data principles are described. By the end of the course, students will be able to recognize and carefully differentiate between problems unique to data science and those that arise as a result of using other related computational methods of analysis, such as machine learning and artificial intelligence. They will also be able to distinguish between ethical misconduct unique to data science methods and those that may result from the contexts in which these methods are used.
NEURAL NETWORKS AND DEEP LEARNING

Course code

DASC488

Credit

3

Theoretical

3

Practical

1

Ects

6
In this course Artificial Neural Network (ANN), which is a mathematical paradigm imitating biological neural network for reasoning and problem solving is covered. With focus on practice, the course cover ANN models for various real-world applications and offers a hands-on introduction to deep learning tools and techniques. Students do not need to have an extensive math background to understand this course. The course covers McCulloch-Pitts model and basic neural network models, multilayer perceptron, associative memory, self-organizing feature maps, recurrent neural networks, etc. and reviews applications of these models to various types of data. Upon completion of this course, students will gain a broad understanding of the context of neural networks and deep learning, the data demands of deep learning and the parameters for neural networks.
AREA ELECTIVE

Course code

DASCXX5

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE
AREA ELECTIVE

Course code

DASCXX6

Credit

3

Theoretical

3

Practical

0

Ects

5
AREA ELECTIVE

Optional modules

TRNC citizens and TR citizen candidate students who have completed their entire high school education in TRNC. They are placed in undergraduate programs in line with their success in the CIU Student Placement and Scholarship Ranking Exam and the programs they prefer.

Students who are successful in the exam can register from the TRNC Marketing Office.

Applicants can directly apply online to our undergraduate programs using the application portal. Please fill in your details correctly and upload all the required documents listed on the last page of the application form.

Required documents;

  • Completed application form,
  • Higher/Secondary Certificate or equivalents (e.g. O/A’Level, WAEC/NECO),
  • 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,
  • Fully completed and signed CIU Rules and Regulations document (which can be downloaded during the online application).

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.

  Non-Scholarship 50% Scholarship
Undergraduate Programs € 5.843,00 € 3.099,00

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