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Curriculum / Graduation Requirements

The MITB curriculum has its courses classified into the following series:

 
*
A compulsory pre-requisite course is required.
These courses cannot be taken in students' first term of study. As a result, some full-time students may need to extend to their fourth term of study in order to read these courses. Only those with special exemptions can be allowed to read these courses in the first term of study.
§
The AI Translational Research Seminar is a graduation requirement (without credit) for AI track students.

Course modules listed are subject to change.


GRADUATION REQUIREMENTS FOR ARTIFICIAL INTELLIGENCE TRACK

Students must complete and pass a total of 15 Course Units (CUs) with a minimum cumulative Grade Point Average (GPA) of 2.5 to graduate with the MITB degree.

POSTGRADUATE PROFESSIONAL DEVELOPMENT (1 CU)
POSTGRADUATE PROFESSIONAL DEVELOPMENT Any 4 full-day topics across the categories here
PROGRAMME CORE (1 CU)
TECH Spreadsheet Modelling for Decision Making
TRACK CORE (4 CUs)
AI Algorithm Design & Implementation
AI Introduction to Artificial Intelligence*
AI Applied Machine Learning*
AI Choose either:
AI Planning & Decision Making*
or Multi-Agent Systems*
TRACK ELECTIVES (5 CUs)
ANALYTICS Choose any 1 CU
ANALYTICS Choose either:
Big Data: Tools & Techniques
or Data Management
AI Choose any 2 CUs
TECH Choose any 1 CU
OPEN ELECTIVES (4 CUs)
OPEN ELECTIVES Choose any 4 CUs from the following^:
  • Internship or Capstone Project (2 CUs)
  • Courses from any series in the MITB curriculum
  • Courses from other SMU Masters programmes (up to 2 CUs)
^
Students are strongly encouraged to take up an immersive component (such as an Internship, Capstone Project or SMU-X course) during their study at MITB.

Last updated on 03 Sep 2021 .