| Course Level: | Master's | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | 4 Year Bachelor’s Degree | |
Choosing the MS in Data Science at Seoul National University (SNU) offers a world-class education in one of Asia's leading institutions. SNU's cutting-edge curriculum, led by renowned faculty, equips students with both theoretical knowledge and practical skills in data analytics, machine learning, and AI. The program emphasizes research, innovation, and hands-on experience, providing access to advanced technologies and data-driven industries. Located in the tech hub of South Korea, students benefit from strong industry connections, networking opportunities, and potential collaborations with top companies, making SNU an excellent choice for those aspiring to become data science leaders.
Category |
Details |
|---|---|
|
Program Name |
MS in Data Science |
|
Degree Awarded |
Master of Science (MS) in Data Science |
|
Course Duration |
2 years (typically) |
|
Language of Instruction |
English |
|
Yearly Tuition Fees |
Approximately 9,000,000 KRW (varies depending on the program and student status) |
|
Total Tuition Fees |
Approximately 18,000,000 KRW (for the full program) |
|
Total Program Cost |
Around 20,000,000 to 25,000,000 KRW (including additional costs like living expenses) |
|
Eligibility |
A bachelor’s degree in a related field (e.g., Computer Science, Statistics, Engineering) |
|
Admission Requirements |
Undergraduate degree, GRE (optional), strong academic record, recommendation letters, SOP, and proof of English proficiency (TOEFL/IELTS) |
|
Application Intake |
Typically, in Spring (March) and Fall (September) |
|
Scholarship |
Available for international and domestic students based on merit and financial need |
|
Career Prospects |
High demand for data science professionals in sectors like tech, finance, healthcare, and research. Graduates often find roles as data scientists, analysts, or engineers in top companies globally |
|
Curriculum Structure |
Core subjects in statistics, machine learning, programming, and data analytics. Electives focus on specialized topics such as AI, big data, and deep learning |
