Master of Data Science (MDataSc)
Master of Data Science (MDataSc)
Program Code
MDSCI
Program Faculty
Faculty of Sciences, Engineering and Technology
Academic Year
2023
These Program Rules should be read in conjunction with the University's policies (https://www.adelaide.edu.au/policies).
Overview
The Master of Data Science is a conversion program designed for students who wish to develop new skills in the growing area of data science, with a specific focus on largescale data analysis, or big data. In this program, students undertake a variety of core and elective courses, designed to combine skills in computer science, mathematics, data science and data science analysis, as well as a significant project designed to combined skills developed across the program.
The program provides the necessary skills for entering the world of Big Data and Data Science, an emerging area of necessity for many fields, including Science, Engineering, Economics and Digital Humanities. The program will help learners understand how data is changing our world, and how learners can apply data science techniques to drive changes in their organisation or area. The program will provide an introduction to emerging field of data, and introduce fundamental analysis techniques, explored through a range of case studies, gaining deeper knowledge of relevant computational and mathematical techniques, such as machine learning and data mining.
The Master of Data Science is an AQF Level 9 Qualification with a standard fulltime duration of 2 years.
Conditions
Condition of Enrolment
Interruption of program: Students must apply for permission from the Executive Dean or delegate before taking a Leave of Absence. Any extension of the leave without approval will result in the loss of place in the program but an application may be made to be readmitted to the program subject to the admission procedures in place at the time.
Academic Program Rules for Master of Data Science
There shall be a Master of Data Science.
Qualification Requirements
To qualify for the degree of Master of Data Science, the student must complete satisfactorily a program of study consisting of the following requirements with a combined total of not less than 48 units comprising:
 Core courses to the value of 15 units
 A research project to the value of 12 units
 Elective courses to the value of 21 units
 Unless exempted international students are required to take ENG 7057 Communication & Critical Thinking in lieu of an elective.
Core Courses

Core Courses
To satisfy the requirements for Core Courses students must complete courses to the value of 15 units.
All of the following courses must be completed:
Subject/Catalogue Course Title Unit Value COMP SCI 7210 Foundations of Computer Science A 3 COMP SCI 7211 Foundations of Computer Science B 3 MATHS 7027 Mathematical Foundations of Data Science 3 MATHS 7107 Data Taming 3 STATS 7022 Data Science PG 3 
Research Project
To satisfy the requirements for Research Project students must complete courses to the value of 12 units.
All of the following courses must be completed:
Subject/Catalogue Course Title Unit Value MATHS 7097A Data Science Research Project Part A 0 MATHS 7097B Data Science Research Project Part B 12
Electives

Electives
To satisfy the requirements for Electives students must complete courses to the value of 21 units.
Courses to the value of 15 units from the following:
Subject/Catalogue Course Title Unit Value APP MTH 7124 Decision Science PG 3 COMP SCI 7212 Human and Ethical Factors in Computer Science 3 COMP SCI 7314 Introduction to Statistical Machine Learning 3 COMP SCI 7318 Deep Learning Fundamentals 3 COMP SCI 7416 Applied Machine Learning 3 ENG 7111 Internship 6 MATHS 7103 Probability & Statistics PG 3 MATHS 7105 Data Literacy 3 and
Courses to the value of 6 units from the following:
Subject/Catalogue Course Title Unit Value COMP SCI 7007 Specialised Programming 3 COMP SCI 7059 Artificial Intelligence 3 COMP SCI 7076 Distributed Systems 3 COMP SCI 7088 Systems Programming 3 COMP SCI 7201 Algorithm & Data Structure Analysis 3 COMP SCI 7208 Programming and Computational Thinking for Data Science 6 COMP SCI 7209 Big Data Analysis and Project 3 COMP SCI 7305 Parallel and Distributed Computing 3 COMP SCI 7306 Mining Big Data 3 COMP SCI 7317 Using Machine Learning Tools PG 3 COMP SCI 7407 Advanced Algorithms 3 COMP SCI 7416 Applied Machine Learning 3 COMP SCI 7417 Applied Natural Language Processing 3 PHIL 7005 Machine Learning and Artificial Intelligence 3 STATS 7054 Statistical Modelling 3 STATS 7107 Statistical Modelling and Inference 3 or
With the approval of the Program Director, courses to the value of 6 units from the following:
Subject/Catalogue Course Title Unit Value APP MTH 7044 Applied Mathematics Topic C 3 APP MTH 7045 Applied Mathematics Topic B 3 APP MTH 7048 Applied Mathematics Topic A 3 APP MTH 7049 Applied Mathematics Topic D 3 APP MTH 7087 Applied Mathematics Topic E 3 APP MTH 7088 Applied Mathematics Topic F 3 MATHS 7026 Cryptography PG 3 STATS 7004 Statistics Topic A 3 STATS 7008 Statistics Topic D 3