| Course Level: | Master's | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | 4 Year Bachelor’s Degree | |
| First Year Total Fees: | $ 18000(₹ 2200000) | |
| Total Course Fees: | $ 36000(₹ 4800000) | |
Choosing an M.Tech in Machine Learning at Ulsan National Institute of Science & Technology (UNIST) offers a unique opportunity to study at a prestigious institution in South Korea. UNIST is renowned for its cutting-edge research in artificial intelligence, robotics, and machine learning, providing students with access to state-of-the-art labs and expert faculty. The program combines theoretical foundations with practical applications, ensuring students are well-prepared for global industry demands. Additionally, South Korea’s growing tech industry offers ample opportunities for internships and collaborations, making it an ideal choice for aspiring machine learning professionals.
Category |
Details |
|---|---|
|
Program Name |
M.Tech in Machine Learning |
|
Degree Awarded |
Master of Technology (M.Tech) |
|
Course Duration |
2 years |
|
Language of Instruction |
English |
|
Yearly Tuition Fees |
Approx. KRW 10,000,000 (~USD 8,000) |
|
Total Tuition Fees |
Approx. KRW 20,000,000 (~USD 16,000) |
|
Total Program Cost |
Approx. KRW 25,000,000 to 30,000,000 (~USD 20,000 to 24,000) (Including living expenses and additional fees) |
|
Eligibility |
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field |
|
Admission Requirements |
Completed online application, academic transcripts, recommendation letters, English proficiency test (TOEFL/IELTS), Statement of Purpose (SOP), CV/Resume |
|
Application Intake |
Typically in Spring (March) and Fall (September) |
|
Scholarships |
Merit-based scholarships available (up to full tuition coverage) |
|
Career Prospects |
Opportunities in tech companies, research institutions, AI startups, data science, machine learning engineering, robotics, and automation industries |
|
Curriculum Structure |
Core courses (Machine Learning, AI Fundamentals, Data Science), elective courses (Deep Learning, Computer Vision, Natural Language Processing), thesis/project work |
