FAQ | MS Stat Data Science

FAQ

ADMISSION

 

1. Who should apply for MS in Statistics?

    Anyone interested in advancing his or her career or changing career paths by developing data science and statistical analysis skills is encouraged to apply.

2. What are the requirements for MS in Statistics?

    Applicants for MS program in Statistics must have:
    (1) A bachelor’s degree of any major
    (2) At least 12 credits of quantitative coursework (i.e., mathematics, linear algebra, probability/statistics, quantitative analysis etc.)

3. Is work experience required?

    It is required for only the Part-time program (at least 1 year of work experience as of August 1st, academic year the applicant enters the program).  The internship during applicant's college years cannot be counted toward work experience.

4. What are the minimum CUBEST, GRE, and GMAT scores required for admission?

    There are no set minimum scores for admission.  Applicant’s scores will be evaluated in the context of other applicants. We review applicants' materials as a whole, not simply a measure of scores.  The test scores must be valid until August 1st, academic year the applicant enters the program.

5. How long does it take to complete the program?

    Typically, students complete the program in 2 academic years.

6. How many seats the program offers each year?

    Currently, the program plans to take 10-20 full-time students and 20-40 part-time students each year.  However, the number is subject to change without prior notice.

 

APPLICATION

 

1.What is the application deadline?

    The deadline for academic programs is May 22nd.

2. How do I apply to the MS in Statistics?

    - For Full-time program, all applicants must submit application materials online via www.grad.chula.ac.th.
    - For Part-time program, application materials must be sent to 

      MS in Statistics
      Department of Statistics
      9th Floor, Mahitalathibhet Building
      Chulalongkorn Business School
      Phyathai Road, Pathumwan, Bangkok 10330

3. Is it possible to waive English Proficiency Test Score?

    Yes, the English Proficiency Test Score can be waived if you completed a (graduate or postgraduate) degree in an international program or oversea.

4. Is it possible to waive CUBEST, GRE, or GMAT requirement?

    No, the aptitude test score cannot be waived.

5. Is it possible to waive core courses?

    No, all the core courses cannot be waived.

6. How can my references submit their letters of recommendation?

    Two reference letters can be submitted in paper format but must be sealed in an envelope. It is highly recommended that at least one letter is from an academic.

 

FINANCIAL

 

1. What are the tuition costs?

    The MS in Statistics tuition is 24,500 baht per semesterfor for the Full-time program and 69,500 baht per semester for the Part-time program. (2 semesters per 1 academic year)

2. Is financial aid available?

    Some financial aid might be given to selected students in a form of research assistantship or teaching assistantship.

 

What is Data Science

 

1. Definition from Wikipedia:

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.

Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, information science, and computer science.

2. Definition from datarobot .com

Data science is the field of study that combines domain expertise, programming skills, and knowledge of math and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems that perform tasks which ordinarily require human intelligence. In turn, these systems generate insights that analysts and business users translate into tangible business value.