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Fall 2023 Applications Are Still Open!
Fall & Spring 2023 Applications Are Still Open!

Master of Science – Data Science (Thesis) at Yeditepe University: Tuition: $15000 USD Full Program (Scholarship Available)

In recent years, especially social media and information technologies playing a bigger role in our lives have changed the perspective of many disciplines on digital data. As in the past, the information technology tools designed by software companies are no longer able to adapt to the forms of large-scale data that changes every day and cannot provide fast solutions to the demands of the changing analytical world. With the rapidly developing information technologies, complex data can be analyzed with flexible programming systems that are easy to use and learn, and digital data that could not be stored in data warehouses before can be made available to the user very quickly with cloud systems. As a result,

The data science master's program aims to train scientists who can control, change and shape large-scale data, and research which mathematical, statistical or machine learning method can better examine the data.

Educational Objectives The
data science master's program aims to train scientists who can control, change and shape large-scale data, and research which mathematical, statistical or machine learning method can better examine the data.

Outcomes of the Master's Program Graduates of the
Data Science “Master's Programme” are expected to have the following competencies:

1. Reaches the information broadly and in depth by doing scientific research in the field of Data Science, evaluates, interprets and applies the information.
2. Complements and applies knowledge with scientific methods using limited or incomplete data; integrates knowledge from different disciplines.
3. Constructs Data Science problems, develops methods to solve them and applies innovative methods in solutions.
4. Develops new and/or original ideas and algorithms; develops innovative solutions in system, part or process designs.
5. Has comprehensive knowledge about current techniques and methods applied in Data Science and their limitations.
6. Designs and implements analytical, modeling and empirical research; analyze and interpret the complex situations encountered in this process.
7. Communicate verbally and in writing using a foreign language (English) at least at the B2 General Level of the European Language Portfolio.
8. Leads multi-disciplinary teams, develops solution approaches in complex situations and takes responsibility.
9. Presents the processes and results of Data Science studies in a systematic and clear way in written or verbal form in national and international environments in or outside the field.
10. Observes social, scientific and ethical values ​​in the stages of data collection, interpretation, announcement and in all professional activities.
11. Be aware of new and emerging applications of Data Science, examine and learn them when necessary.

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