| Course Level: | Master's | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | 3 Year Bachelor’s Degree | |
| First Year Total Fees: | $ 5000(₹ 400000) | |
| Total Course Fees: | $ 10000(₹ 800000) | |
Choosing an MS in Artificial Intelligence at Konyang University, South Korea, offers a strong blend of advanced research, practical learning, and global exposure. The university provides state-of-the-art AI laboratories, expert faculty, and collaboration opportunities with leading tech industries. Its curriculum focuses on deep learning, machine learning, robotics, and data science, preparing students for innovation-driven careers. Konyang’s emphasis on hands-on projects and interdisciplinary learning fosters problem-solving and creativity. Located in a technologically advanced nation, the program also offers cultural diversity, research funding, and pathways to global AI careers in academia, industry, and research institutions.
Particulars |
Details |
|---|---|
|
Program Name |
Master of Science in Artificial Intelligence |
|
Degree Awarded |
M.S. in Artificial Intelligence |
|
Course Duration |
2 years (4 semesters) |
|
Language of Instruction |
English / Korean |
|
Yearly Tuition Fees |
Approx. USD 6,000 – 7,000 per year |
|
Total Tuition Fees |
Approx. USD 12,000 – 14,000 for entire program |
|
Total Program Cost (including living expenses) |
Around USD 20,000 – 24,000 |
|
Eligibility |
Bachelor’s degree in Computer Science, Engineering, or related field |
|
Admission Requirements |
Completed application form, transcripts, degree certificate, English proficiency (TOEFL/IELTS) or Korean (TOPIK), statement of purpose, recommendation letters |
|
Application Intake |
Spring (March) and Fall (September) |
|
Scholarship |
University and government scholarships available based on merit and academic performance |
|
Career Prospects |
AI Engineer, Data Scientist, Machine Learning Researcher, Robotics Engineer, AI Consultant, Research Analyst |
|
Curriculum Structure |
Core courses: Machine Learning, Deep Learning, Data Mining, Neural Networks; Electives: Natural Language Processing, Computer Vision, AI Ethics; Thesis or Research Project in final semester |
.png)
