Program Description

This unique one-year graduate program (non-thesis) for Data Analytics is designed for working professionals. They will have the opportunity to build their network and learn from their full-time and part-time instructors along with other business professionals who take part in their classes as well as their fellow classmates in their cohort and the alumni network of Sabanci University. The language of instruction is English.

Program Objectives

Data Analytics is considered to be a relatively new field which integrates state-of-the-art computational and statistical techniques to extract business value from a rapidly expanding volume of data. This program is designed to help our participants develop the skill set needed for creating and maintaining the added competitive edge that innovative companies are trying to establish. Our curriculum will help the students develop skills required for data-driven decision-making with a wide variety of courses such as: Introduction to Data Analytics using Python, Data Management and Processing, Machine Learning, Practical Case Studies in Data Analytics, Applied Statistics, Optimization, Decision Modeling, Exploratory Data Analysis and Visualization, Social Network Analysis, Project Management and Business Communication, etc.

Qualification Awarded

The Master 's Degree in Data Analytics ( second cycle inData Analytics) is awarded to the graduates who have successfully completed all courses in the curriculum.

Level of Qualification

Second Cycle

Specific Admission Requirements

The general requirements explained in “Quotas and Admissions” of Instruction Letter For Sabancı Unıversity Graduate Programs for admission of students.

Qualification Requirements and Regulations

Students must obtain a grade point average of at least 3.00 out of 4.00 and successfully pass all courses on the programme.

Recognition of Prior Learnin

Exemptness from the courses which are included in transfer and student exchange programs are regulated by the related articles in Information on the Instruction Letter For Sabancı Unıversity Graduate.
At Sabancı University, apart from formal education institutions, there is no recognition process for informal-based or experience-based (in-formal and non-formal) learning.

Program Outcomes

  1. Comprehend the conceptual foundations of analytical methods and techniques within the scope of business analytics,
  2. Acquire theoretical and practical knowledge on applied information systems by developing fundamental programming skills,
  3. Improve decision making by turning high-volume data into useful information and integrating data analysis tools,
  4. Turn high-volume data into useful information by using quantitative models and understanding and managing data analysis techniques, communicate and visualize the results for business use,
  5. Understand the data quality, data integrity and data accuracy concepts, and occupational ethics regarding data privacy and intellectual property.

Occupational Profiles of Graduates

  • Data Scientist
  • Machine Learning Expert
  • Data Translator
  • Data Analyst
  • Chief Data Officer (CDO)

Access to Further Studies

The general requirements explained in “Quotas and Admissions” of Information on the Instruction Letter For Sabancı Unıversity Graduate Programs for acceptance of the students to be taken to the graduate programs.

Exam Regulations and Assessment & Grading

The evaluation and grading of each course is included in “Examinations & Academic Assessment and Grades” of Information on the Instruction Letter For Sabancı Unıversity Graduate for admission of students.

Graduation Requirements

Graduation requirements are explained in the Instruction Letter For Sabancı Unıversity Graduate for admission of students.

Mode of Study

Full-Time

Program Coordinator

Hasan Sait Ölmez-sait.olmez@sabanciuniv.edu