Study Master of Science in Data Science at Wright State University in the USA,
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Master of Science in Data Science

USA

What will I learn?

The Master of Science in Data Science program allows you to develop knowledge and skills across the disciplines of computer science and statistics. You will understand the theory and design of statistical methods and models, as well as computing systems and algorithms, empowering them with the ability to make informed decisions in their exploration and testing of data. You will also devise methods, systems, and architectures for information discovery and have the foundations to learn and understand state-of-the-art developments in this rapidly evolving field.

Study options

Full Time (4 Semesters)

Tuition fees
US$13,740.00 per year
Annual Living Expenses - 10200

*Price shown is for indicative purposes, please check with institution

Start date

January 2027

Venue

Dayton Campus

3640 Colonel Glenn Hwy,

Dayton,

Ohio,

45435, Midwest, United States

Full Time (4 Semesters)

Tuition fees
US$13,740.00 per year
Annual Living Expenses - 11000

*Price shown is for indicative purposes, please check with institution

Start date

August 2027

Venue

Dayton Campus

3640 Colonel Glenn Hwy,

Dayton,

Ohio,

45435, Midwest, United States

Entry requirements

For international students

You must submit an official transcript accompanied by a translation into English if needed. If your credentials cannot be evaluated by the Office of International Admissions, you are required to submit your academic credentials to an evaluation service and pay the cost of the evaluation.

*There may be different IELTS requirements depending on your chosen course.

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About Wright State University

Whether you want to be a scientist, artist, engineer, doctor, or business leader, there’s an outstanding academic program for every learner.

  • Two campuses in affordable Ohio locations
  • 16:1 student-to-faculty ratio
  • US ranked business, engineering, and nursing programs
  • Many experiential-learning opportunities

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