The electives in this list will form part of the general programme in Data Science provided the time table allows this, as well as the schedules for assessments. The number of credits reserved for the compulsory modules and the number of credits available for electives from different data rich environments in each study-year, are as follows:

THE FIRST YEAR: Compulsory modules (credits, semester)

Probability Theory and Statistics 114 (16, semester 1)

Mathematics [Calculus] 114  (16, semester 1)

Mathematics [Calculus and linear algebra] 144 (16, semester 2)

Computer Science [Introductory Computer Science] 113 (16, semester 1)

Computer Science [Introductory Computer Science] 144 (16, semester 2)

Data Science 141 (16, semester 2)

THE SECOND YEAR: Compulsory modules (credits, semester)

Mathematical Statistics [Distribution theory and introduction to statistical inference] 214 (16, semester 1)

Mathematical Statistics [Statistical inference] 245  (8, semester 2)

Mathematical Statistics [Linear models in Statistics] 246 (8, semester 2)

Mathematics [Advanced calculus and linear algebra] 214 (16, semester 1)

Computer Science [Data structures and algorithms] 214 (16, semester 1)

Computer Science [Computer architecture] 244 (16, semester 2)

Data Science 241 (16, semester 2)

THE THIRD YEAR: Compulsory modules (credits, semester)

Mathematical statistics [Statistical inference and probability theory] 312 (16, semester 1)

Computer Science [Machine learning] 315 (16, semester 1)

Computer Science [Program design] 344 (16, semester 2)

Data Science 314 (16, semester 1)

Data Science 344 (16, semester 2

THE FOURTH YEAR: Compulsory (credits, semester)

Introduction to Statistical Learning 4XX (12, semester 1)

Data Science Research assignment 471 (40, semester 1&2)