Data Science and Analytics PGDip Program

The Post Graduate Diploma (PGDip) is awarded upon successful completion of a minimum of 30 credits with a minimum of 3.0 cumulative GPA. Courses require a minimum of B- for course credit.

Duration of Study

Students must complete the PGDip in Semesters and 1 Summer Session. Students are not permitted to change tracks.

PGDip Program Requirements

The PGDip program has the following components:

English Courses (6 credits)
Core Courses (18 credits)
Capstone Project (6 credits)
Winter Enrichment Program* (WE 100) (non-credit)

*Students must successfully complete the Micro-Credential in Python, offered as part of WEP, to receive a Satisfactory (S) grade.

Course Requirements (24 credits)

Semester 1:
ENG 100	Advanced English Language Communication	3
CEMSE 101	Engineering Mathematics	3
CEMSE 143	Introduction to Probability and Statistics	3
CEMSE 151	Linear Algebra	3

Semester 2:
ENG 101	Critical Writing Discussion & Debate	3
CS 201	Introduction to Programming with Python	3
Choose two:
CEMSE 131	Vector Calculus and Ordinary Differential Equations	3
CS 204	Data Structures and Algorithms	3
ECE 151	Signals and Systems I	3
STAT 210	Applied Statistics and Data Analytics	3

Students who fail any of the course requirements will be dismissed from the PGDip Program. Given the sequential nature of the course offering, appeals are not considered.

Students can transfer 200-level credits earned during the PGDip to the KAUST MS degree. However, credits from CS 201 and CS 204 do not count towards the MS degree in the Computer Science (CS) Program.

Capstone Project (6 credits)

During the Summer Session, all PGDip students must register for 6 credits of Capstone Project. The project's topic should be related to Machine Learning, Data Analytics, Bioinformatics, or IoT and Embedded Systems. Students can also partake in an on-campus/off-campus internship at start-ups (in collaboration with the Entrepreneurship Center).