CBK91916 Electives
Students in the Master of Data Science and Innovation course may undertake a maximum of one approved undergraduate subject as an elective. The subjects in this choice block are all Postgraduate level subjects.
Completion requirements
| Select 20 credit points of options: | 20cp | ||
| CBK91917 Free Electives | 12cp | ||
| CBK91986 Free Electives | 12cp | ||
| 37457 Advanced Bayesian Methods | 8cp | ||
| 32513 Advanced Data Analytics Algorithms | 6cp | ||
| 36125 Advanced Data Science for Innovation | 2cp | ||
| 32113 Advanced Database | 6cp | ||
| 36120 Advanced Machine Learning Application | 8cp | ||
| 36119 Advanced Topics in Data Science | 4cp | ||
| 36124 Applied Data Science for Innovation | 2cp | ||
| 36118 Applied Natural Language Processing | 8cp | ||
| 36121 Artificial Intelligence Principles and Applications | 8cp | ||
| 94693 Big Data Engineering | 8cp | ||
| 42904 Cloud Computing and Software as a Service | 6cp | ||
| 94697 Data Science Internship A | 6cp | ||
| 94698 Data Science Internship B | 6cp | ||
| 94692 Data Science Practice | 8cp | ||
| 36109 Data and Decision Making | 8cp | ||
| 32606 Database | 6cp | ||
| 94691 Deep Learning | 8cp | ||
| 33116 Design, Data, and Decisions | 6cp | ||
| 32130 Fundamentals of Data Analytics | 6cp | ||
| 94699 Innovation Lab: Internship Project | 8cp | ||
| 37242 Introduction to Optimisation | 6cp | ||
| 36101 Leading Data Science Initiatives | 8cp | ||
| 15315 Project Management Principles | 6cp | ||
| 36122 Python Programming | 8cp | ||
| 37252 Regression and Linear Models | 6cp | ||
| 36123 Research Paper 1 | 8cp | ||
| 36102 Research Paper 2 | 12cp | ||
| 42913 Social and Information Network Analysis | 6cp | ||
| 94689 Special Subject 1 (FTDI) | 2cp | ||
| 37495 Statistical Design and Models for Evaluation Studies | 6cp | ||
| 32547 UNIX Systems Programming | 6cp | ||
| 60117 Understanding Data and Statistical Design | 6cp | ||
| Total | 20cp |