Program Description

With the advancement of industry and technology, computer capacities have grown exponentially, leading to the measurement and storage of virtually everything. The analysis of large amounts of collected data and the elimination of mechanisms involving uncertainty in events have always been the tasks of Mathematical-Statistical Science. The importance of data-driven knowledge acquisition has grown, leading to the development of Data Science techniques aimed at evaluating collected data in real-time, taking appropriate actions based on analyses, and making predictions about the future. As an interdisciplinary field combining Mathematics, Statistics, and Computer Engineering, Data Science has become more important and popular than ever before.

As a result of these developments, leading universities around the world have added Data Science departments to their Master's programs. Data Science encompasses methods at the intersection of computational artificial intelligence, machine learning, statistics, and database systems. Graduates of these Master's Programs around the world easily find jobs in business, government, financial services, biology, medicine, risk and intelligence, science and engineering, and data mining.

The Data Science Master's Program at Istanbul Gedik University differs from other similar programs in that it focuses not only on Data Science Techniques but also on Data Analysis theory. As is well known, theory without practice and practice without theory are not sufficient. Mathematical-statistical knowledge, when taught as pure theory, does not prepare students to become problem-solving professionals in practice.

Program Structure

The Statistics and Data Science Non-Thesis Master's Program consists of a total of 30 credits, including 10 courses and a term project. The term project is not credited and is graded as either successful or unsuccessful. The duration of the non-thesis master's program is a minimum of two and a maximum of three semesters. The scientific preparation program is not taken into account in the calculation of the duration. Semesters in which the student is not enrolled are included in the maximum duration. There are a total of seven different areas of specialization in the Statistics and Data Science Non-Thesis Master's Program. These are as follows:

1. Applied Statistics
2. Econometrics and Finance
3. Sports and Health
4. Environmental Science
5. Data Mining and Machine Learning
6. Big Data Analysis and Neural Networks
7. Cybersecurity