• # Rating - 4.8 Points
  • # Accomodation #
  • # Scholarship #
  • # Part Time Work #

M.Tech in Artificial Intelligence

Course Level: Master's
Course Duration: 2 Years
Course Language English
Required Degree 4 Year Bachelor’s Degree

Why Choose M.Tech in Artificial Intelligence at Kyung Hee University (KHU)Seoul Campus, South Korea

Pursuing an M.Tech in Artificial Intelligence at Kyung Hee University (KHU), Seoul Campus, offers a unique blend of academic excellence, cutting-edge research, and global exposure. KHU is renowned for its strong emphasis on innovation and interdisciplinary learning, providing students with access to advanced AI labs, experienced faculty, and industry collaborations. Located in Seoul, a global hub for technology and startups, students gain opportunities to engage with leading companies and real-world projects. The program nurtures both technical expertise and creative problem-solving skills, preparing graduates for impactful careers in AI research, development, and leadership roles in the rapidly evolving tech landscape.


M.Tech in Artificial Intelligence at Kyung Hee University (KHU)Seoul Campus, South Korea, Program Details
 

Category

Details

Program Name

M.Tech in Artificial Intelligence

Degree Awarded

Master of Technology (M.Tech)

Course Duration

2 years (4 semesters)

Language of Instruction

English (some elective courses may be in Korean)

Yearly Tuition Fees

Approx. USD 6,000 – 7,000

Total Tuition Fees

Approx. USD 12,000 – 14,000

Total Program Cost

Approx. USD 18,000 – 22,000 (including living expenses)

Eligibility

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field

Admission Requirements

Academic transcripts, English proficiency test (TOEFL/IELTS), recommendation letters, statement of purpose, CV

Application Intake

Spring (March) and Fall (September)

Scholarship

Merit-based, need-based, and Global Korea Scholarships (GKS) available

Career Prospects

AI Engineer, Data Scientist, Machine Learning Specialist, Researcher, PhD pathway

Curriculum Structure

Core courses (AI fundamentals, machine learning, deep learning), electives (NLP, robotics, computer vision), research project, thesis