| Course Level: | Master's | |
|---|---|---|
| Course Duration: | 2 Years | |
| Course Language | English | |
| Required Degree | 3 Year Bachelor’s Degree | |
| First Year Total Fees: | $ 4000(₹ 370000) | |
| Total Course Fees: | $ 8000(₹ 740000) | |
Choosing an MS in Data Science at Gangneung-Wonju National University (GWNU), South Korea, offers a unique blend of advanced education and practical experience. GWNU provides a cutting-edge curriculum covering machine learning, big data analytics, and AI, paired with hands-on projects and industry collaborations. Students benefit from access to modern labs, research centers, and experienced faculty, fostering innovation and problem-solving skills. South Korea’s thriving tech ecosystem provides ample internship and career opportunities. Additionally, GWNU emphasizes global exposure, cultural diversity, and personal growth, making it an ideal environment for aspiring data scientists to develop technical expertise and competitive edge in the international job market.
Category |
Details |
|---|---|
|
Program Name |
Master of Science in Data Science |
|
Degree Awarded |
MS (Master of Science) in Data Science |
|
Course Duration |
2 years (4 semesters) |
|
Language of Instruction |
English / Korean (varies by course) |
|
Yearly Tuition Fees |
Approx. 4,000 – 5,000 USD per year |
|
Total Tuition Fees |
Approx. 8,000 – 10,000 USD |
|
Total Program Cost (Including Living Expenses) |
Approx. 15,000 – 20,000 USD |
|
Eligibility |
Bachelor’s degree in CS, IT, Mathematics, Statistics, or related field; minimum GPA 2.5/4.0 |
|
Admission Requirements |
Academic transcripts, CV, Statement of Purpose, 2 Letters of Recommendation, English proficiency (TOEFL/IELTS) |
|
Application Intake |
Spring (March) and Fall (September) |
|
Scholarship |
Merit-based scholarships covering 30–100% tuition; research assistantships may be available |
|
Career Prospects |
Data Scientist, Machine Learning Engineer, Business Analyst, Big Data Analyst, AI Specialist |
|
Curriculum Structure |
Core courses: Machine Learning, Data Mining, Big Data Analytics, AI, Statistics; Electives: Deep Learning, NLP, Data Visualization; Thesis/Capstone Project |
