KAIST College of Business, certified by four international organizations2018-06-07Hit:2273
Establish a strong network with 8300 graduates
KAIST College of Business opened its first full-time MBA in Korea in 1995. The MBA program aims to cultivate professionals who are versatile in both technology and management by utilizing the benefits of being Korea’s top engineering research school. KAIST is the only domestic university certified by four international organizations (AACSB, GMAC, EQUIS, PIM). According to the rankings of "Executive Education Management Schools" by the Financial Times in the UK, KAIST was ranked first in Asia for five consecutive years until 2016, and the world ranking was 21st at that time.
KAIST explained that its world-class faculty closely supervises students. Through its system of supervision, KAIST help students adapt to school life and conduct in-depth research. The KAIST MBA provides individualized research labs to all full-time students 24 hours a day. In addition, KAIST runs its Reuters Trading Center, the largest financial training facility in Korea, and KOSCOM Financial Information Center, which can search real-time financial information from all over the world. Another advantage is that all full-time students can stay in the dormitory.
The alumni network is also an asset of KAIST College of Business. The Alumni network consists of the 8,300 graduates who have gone through KAIST MBA over the last 22 years. The school emphasizes that KAIST graduates are working as top managers in many global and domestic major companies. Moreover, KAIST College of Business produces the largest number of business professors in Korea, specifically, 45% of the graduates of management engineering are employed as university professors.
KAIST College of Business has been leading management education through continuous education innovation that reflects the changes in social and management trends. Moreover, KAIST specializes in training convergent individuals who are able to combine knowledge of both technology and management. Focusing on the 'Fourth Industry Revolution' which will revolutionize the current economy, KAIST MBA program is striving to train business experts by strengthening its curriculum, and this includes Business Analytics as well as Entrepreneurship.
The Techno MBA program, which is the first two-year full time MBA program in Korea, has designated its Business Analytics course as a requirement in order to ensure that students are versatile professionals. Beyond the conceptual understanding, the course provides lessons to develop in-depth skills for understanding and analyzing big data for programming and statistical analysis. Throughout intensive courses, Techno MBA cultivates talented people who can scientifically solve major business problems and systematically establish management strategies.
The Information and Media MBA educate students to derive management insight through the analysis of large-scale data on the Internet of Things (IoT) -based environment. The IMMBA program improves students’ practical ability as well as integrated insights through various courses that enable students to learn how to design databases and experiments, collect actual data, and use statistical analysis techniques examine data.
The Financial MBA strengthened its curriculum on financial programming and financial data analysis to foster financial professionals with the ability to analyze financial big data in line with the rise of the Fintech industry.
The Master of Financial Engineering, which provides in-depth financial analytics courses, offered the Financial and IT Convergence Education Program in cooperation with KAIST's Computer Science Department to train experts in the field of Fintech. This program provide various courses on financial big data analysis such as Financial Statistical Analysis Using R, Financial Econometric Analysis Using Python, Financial Engineering Program and Algorithms, Computer Finance for Learning Databases and Numeric Analysis, Financial AI (artificial intelligence) and Machine Learning, Financial Big Data Analysis, and Credit Risk Big Data Analysis.