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BIG DATA ANALYTICS ASSOCIATE`S (SHORT CYCLE) DEGREE PROGRAMME

Qualification Awarded
Length of Programme (Year)
Total Number of ECTS Credits
Type of Education
Level of Qualification & Field of Study


Associate (Short Cycle) Degree


2


120


Full Time
  • TQF Qualification Type: Associate Degree
  • TQF, TQF-HE, EQF-LLL, ISCED (2011): Level 5
  • QF-EHEA: Short Cycle
  • Yönelim: Vocational
  • Sınıflandırma (ISCED 2013):054,061 Temel Öğrenme Alanı:46,48,52
  • Kategori: Ana Yeterlilik

GENERAL INFORMATION

With the acceleration of digitalization today, data has become a strategic resource in all sectors. Institutions and organizations need experts who can accurately analyze big data, extract meaning from it, and integrate it into decision-making processes to gain competitive advantage. Therefore, developing competent individuals in the field of big data has become one of the most important educational objectives of our time.

The Big Data Analytics Program was created to address this need and aims to equip students with the knowledge and skills necessary for today's requirements in subjects such as data science, data analytics, database management, data visualization, machine learning, and artificial intelligence. The program curriculum is constantly updated in line with current technological developments in the field and structured to meet industry expectations.

The Big Data Analytics Program, which accepts students based on the TYT score type, offers a comprehensive learning process supported by practical training opportunities to train qualified data analysts for the industry.

The Big Data Analytics Program's Vision
To be a leading and respected program preferred by industry and academia by training individuals who closely follow innovations in data science and big data analytics, adhere to ethical values, are creative and analytical thinkers, and can actively participate in data-driven decision-making processes.

The Big Data Analytics Program's Mission
To train qualified big data analysts equipped with up-to-date knowledge and skills in areas such as data analytics, database management, big data processing, machine learning, data visualization, and artificial intelligence; who adhere to professional ethics, are prone to teamwork, have strong problem-solving skills, and possess a commitment to lifelong learning.