| Course Level: | Doctorate | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | Master’s Degree | |
| First Year Total Fees: | $ 11000(₹ 850000) | |
| Total Course Fees: | $ 22000(₹ 1700000) | |
Choosing a PhD in Data Science at the University of Ulsan, South Korea, offers a unique opportunity to engage in cutting-edge research in artificial intelligence, machine learning, and big data analytics. The program emphasizes both theoretical foundations and practical applications, fostering innovation in diverse industries. Students benefit from state-of-the-art laboratories, interdisciplinary collaboration, and mentorship from experienced faculty. Located in a technologically advanced city, the university provides access to Korea’s thriving tech ecosystem and global research networks. Graduates gain strong analytical, computational, and problem-solving skills, preparing them for leadership roles in academia, industry, and research worldwide.
Category |
Details |
|---|---|
|
Program Name |
PhD in Data Science |
|
Degree Awarded |
Doctor of Philosophy (PhD) in Data Science |
|
Course Duration |
3–5 years (full-time) |
|
Language of Instruction |
English / Korean (depending on courses) |
|
Yearly Tuition Fees |
Approx. KRW 5,000,000 – 8,000,000 (~USD 3,800 – 6,100) |
|
Total Tuition Fees |
Approx. KRW 15,000,000 – 40,000,000 (~USD 11,500 – 30,500) |
|
Total Program Cost |
Tuition + Living expenses (~USD 20,000 – 40,000 total estimated) |
|
Eligibility |
Master’s degree in Data Science, Computer Science, Statistics, or related field; strong academic record |
|
Admission Requirements |
Academic transcripts, recommendation letters, statement of purpose, CV, proof of English/Korean proficiency (TOPIK/TOEFL/IELTS), research proposal |
|
Application Intake |
Usually Fall (September) and Spring (March) |
|
Scholarship |
University scholarships, research assistantships, Korean Government scholarships (KGSP) |
|
Career Prospects |
Data Scientist, AI Researcher, Machine Learning Engineer, University Faculty, Tech Industry Leader |
|
Curriculum Structure |
Core courses in Machine Learning, Big Data Analytics, AI, Statistics; Electives in Deep Learning, Data Mining, Computational Methods; Research Seminars; Dissertation |
