Data Informatics M.S. (with thesis)

Data Informatics department website

Introduction

The current wind of digital transformation in the world has increased the volume, variety, and velocity of the data that can be turned into benefit and has made it necessary to use data and data-driven decision-making for today's organizations. The trend of increasing productivity, quality, and product diversity with automation and data-centered approaches, commonly referred to as Industry 4.0, can be seen as a result of gains in technologies such as the Internet of Things (IoT), cyber-physical systems, big data, cloud computing, and artificial intelligence. These changes in the industry naturally cause the transformation of society as well. In Society 5.0, which refers to the next stage after hunter-gatherer, agricultural, industrial, and information societies in human history, technologies such as the Internet of Everything (IoE), artificial intelligence, and block-chain affect and shape all areas of life.

Data Informatics emerges as a wide field of study that covers the acquisition, storage, security, integration, distribution, and management of data along with processing it and obtaining useful information from it to increase the efficiency of organizations in operational processes. Data informatics has an interdisciplinary nature. This master's program aims to offer the foundations and skills that will provide this interdisciplinary perspective to the students.

Program Structure

The master's program consists of a deficiency program and the main program. The deficiency program aims to ensure all admitted students have the necessary academic foundation. Students can be exempted from some of the deficiency courses with their advisors and the academic board's decision based on their previously taken courses and grades. The deficiency program can be completed in a maximum of two terms.

Deficiency Courses: 

  • IS 503 Database Concepts and Applications / CENG 302
  • IS 545 Object Oriented Programming and Data Structures / MI 545 /OOP (Ex. BIN 500 or CENG 305) + (EE 441 or CENG 301)
  • DI 591 Probability and Statistics for Data Informatics / BIN 502 / CENG 222
  • DI 592 Mathematics for Data Informatics

The main program, as indicated below, consists of 3 compulsory and 4 elective courses that totals to at least 21 credits along with non-credit thesis and seminar courses: 

  • 3 credit and compulsory courses 
  • At least 4 elective courses 
  • DI 590 Seminar course 
  • DI 599 Thesis course 

Credit Compulsory Courses: 

  • DI 501 / IS 509 Introduction to Data Informatics  
  • DI 502 Data Informatics Project  

Non-Credit Compulsory Courses: 

  • DI 509 / IS 520 Research Methods and Ethics 
  • DI 590  Seminar course 
  • DI 599  Thesis course 

In addition to the compulsory courses, students will be able to take the technical elective courses listed below to be counted towards the required credit hours: 

Elective Courses 

  • DI 514 / IS 580 Data Mining and Knowledge Discovery 
  • DI 520 / IS 786 Data Driven Organizations 
  • DI 521 / IS 788 Digital Transformation: Management, Technology and Organization 
  • DI 515 / IS 787 Big Data  
  • DI 544 / IS 782 Spatial Data Analysis 
  • MMI 701 Multimedia Signal Processing 
  • MMI 702 Machine Learning for Multimedia Informatics 
  • MMI 706 Reinforcement Learning 
  • MMI 726 Multimedia Standards 
  • MMI 727 Deep Learning 
  • IS 533 Decision Support Systems 
  • IS 535 Regulatory and Legal Aspects of Information Systems 
  • IS 543 Information Retrieval 
  • IS 547 Cloud Computing: Technology and Business 
  • IS 566 Image Processing Algorithms 
  • IS 585 Social Network Analysis 
  • IS 710 Energy Informatics 
  • IS 748 Mobile and Pervasive Computing 
  • IS 768 Applications of Audio Information Systems 
  • IS 777 Technology Entrepreneurship and Lean Startups 
  • IS 783 Social Media Analytics 
  • IS 784 Deep Learning for Text Analytics 
  • COGS 515 Artificial Intelligence for Cognitive Science 
  • COGS 516 Introduction to Probabilistic Programming 
  • COGS 566 Probabilistic Models of Cognition 
  • MI 535 Biological Signal Analysis

Application Requirements

Students with any background are welcome to apply to the program. A common academic basis for incoming students is achieved via deficiency courses.

Requirements for your application to be considered:

  • An undergraduate degree from a Turkish university or an equivalent university that the Council of Higher Education recognizes,
  • Having a score of 75 from ALES 75 or 713 from GRE Quantitative (156 in the new system),
  • Having a minimum GPA of 2.5,
  • Having a valid minimum score of 79 from TOEFL iBT, 550 from TOEFL PBT, 6.5 from IELTS, or 65 from METU English Proficiency Exam,
  • Two letters of recommendation,
  • A one-page letter of intent in English

The candidates are invited to interviews based on their ALES (or equivalent) scores and undergraduate. Admission decisions are made based on a holistic review of the scores and the candidate's suitability to the program.

Contact Information about Application

Email: