Students are admitted to KAUST from a wide variety of programs and backgrounds. To facilitate the design of an appropriate study plan for each individual student, all admitted students without an M.Sc. are required to take a written assessment exam when they arrive on campus. The purpose of the assessment is to determine whether students have mastered the prerequisites for undertaking graduate-level courses taught in the program. The academic advisor works with admitted students to develop a study plan if needed. Students are encouraged to prepare for the assessment by refreshing the general knowledge gained from their undergraduate education before arriving at KAUST. The study plan requirements must be satisfactorily completed, in addition to the university degree requirements. The topics covered by the assessment test are: calculus of one and multiple variables, linear algebra, probability, and statistics, at an undergraduate level.
It is the responsibility of students to plan their graduate program in consultation with their academic advisor. Students are required to meet all deadlines. Students should be aware that most core courses are offered only once per year.
The Master of Science (M.Sc.) degree is awarded upon successful completion of a minimum of 36 credit hours. A minimum GPA of 3.0 must be achieved to graduate. Individual courses require a minimum of a B- for course credit. Students are expected to complete the M.Sc. degree in three semesters. Satisfactory participation in every KAUST summer session is mandatory.
The M.Sc. Requirements
- Core courses (12 credits)
- Elective courses (12 credits)
- Research/capstone experience (12 credits)
- Graduate seminar 398 (non-credit) – all students are required to register and receive a satisfactory grade for the first two semesters
- Completion of one Winter Enrichment Program (WEP) – typically during the first year of enrollment
Core Courses (12 credits)
Students enrolled toward the M.Sc. degree (for the two tracks) are required to complete the following 12 credits of core courses:
The core courses are designed to cover the basic skills and competencies that are expected of students holding an advanced degree. STAT 220, STAT 230, STAT 250 are part of the Ph.D. qualifying examination.
Elective Courses (12 credits)
The elective courses (which exclude research, internship credits, and IED courses) are designed to allow students to tailor their educational experience to meet individual research and educational objectives, with the permission of the academic advisor.
Students enrolled toward the M.Sc. degree are required to complete 12 credits of elective courses. Courses from other programs can be taken as elective courses as agreed with the academic advisor. Relevant courses are listed below (but not limited to):
| AMCS 206 | Applied Numerical Methods | 3 |
| AMCS 211 | Numerical Optimization | 3 |
| AMCS 215 | Mathematical Foundations of Machine Learning | 3 |
| CS 207 | Programming Methodology and Abstractions | 3 |
| CS 220 | Data Analytics | 3 |
| CS 229 | Machine Learning | 3 |
| CS 245 | Databases | 3 |
| CS 247 | Scientific Visualization | 3 |
| CS 248 | Computer Graphics | 3 |
| CS 249 | Algorithms in Bioinformatics | 3 |
| CS 260 | Design and Analysis of Algorithms | 3 |
| ECE 242 | Digital Communication and Coding | 3 |
| ECE 251 | Digital Signal Processing and Analysis | 3 |
| ErSE 213 | Inverse Problems | 3 |
| ErSE 222 | Machine Learning in Geoscience | 3 |
| ErSE 253 | Data Analysis in Geosciences | 3 |
Note: For STAT students, STAT 210 can only be taken on a pass/fail basis. Moreover, at most one course among AMCS 201, AMCS 202, AMCS 206 can be taken on a letter grade basis with approval of the academic advisor (students must declare that at the beginning of the semester at the time of registration). STAT Ph.D. students cannot take any of the STAT 210, AMCS 201, AMCS 202, AMCS 206 courses on a letter grade basis.
Specific additional requirements for students in the MS Statistics (Data Science track): they are required to complete CS 229 Machine Learning and at least 6 credits of other elective courses from the CS 200-level
M.Sc. Thesis
The thesis defense committee, which must be approved by the dean, must consist of at least three members and typically includes no more than four members. At least two of the required members must be KAUST faculty. The chair plus one additional faculty member must be affiliated with the student’s program. This membership can be summarized as:
| Member |
Role |
Program Status |
| 1 |
Chair |
Within program |
| 2 |
Faculty |
Within program |
| 3 |
Faculty |
Outside program, inside KAUST |
| 4 |
Optional faculty or research scientist |
Inside or outside KAUST |
Notes:
- Members 1-3 are required, member 4 is optional
- Two members need to have primary affiliation in the CE program
- Co-chairs may serve as member 2, 3, or 4, but may not be a research scientist
- Members 2 and 3 must use primary affiliation only
- Adjunct professors and professors emeriti may retain their roles on current committees, but may not serve as chair on any new committees
- Professors of practice and research professors may serve as members 2, 3 or 4 depending upon their affiliation with the student’s program, they may also serve as co-chairs
- Visiting professors may serve as member 4
View a list of faculty and their affiliations here.
M.Sc. Non-Thesis
Students wishing to pursue the non-thesis option must complete a total of 12 capstone credits, with a maximum of 6 credits of directed research (STAT 299).
Students must complete the remaining credits through one or a combination of the options listed below:
- Broadening experience courses: courses that broaden a student’s M.Sc. experience
- Internship: research-based summer internship (295) – students are only allowed to take one internship
- Ph.D. courses: courses numbered at the 300 level