MC267 - Master of Data Science

Go to Student Program Guide Search

RMIT program code: MC267
Plan name: Master of Data Science
Plan code: MC267
Campus: City Campus
Credit points per semester:
Full time: 48
Part time: 24
CRICOS code: 093313B

Contact details and related links


2019 Enrolment Program Structure

To graduate you must complete the following:

  Year One of Program
 
AND  Year Two of Program
 

- A recommended full-time study load is 48 credit points or Four (4) courses equivalent each semester.

- Total number of credit points needed to complete this master's degree is 192 credit points or 16 courses equivalent.  You can choose one of the following streams:

1. Project Stream:

9 Core Courses
5 Program Option Courses
Data Science Postgraduate Project (24CP)

2. Research Stream:  (minimum CGPA of 3.0 required)

10 Core Courses*
3 Program Option Courses
Minor Thesis (36CP)

*Students planning to take the Minor Thesis/Project must complete COSC2149 Research Methods prior to starting the Minor Thesis/Project. Note: COSC2149 Research Methods is only offered in Semester 1.

 

VERY IMPORTANT ADMINISTRATIVE ESSENTIALS

NEW STUDENTS:

Induction and Orientation Essentials

Before starting your courses in your program, we strongly advise youto complete theAcademic Integrity module and the Lab/Unix Induction program. These skills are essential.

 

CONTINUING STUDENTS:

In 2019 the following changes have been made to this program.

  • New Data Science Program Option Courses added to the list;
  • A new Research stream comprising COSC2149 Research Methods and COSC2179 Minor Thesis (36CP) has been added (along with part-time option);
  • COSC2669 Legal, Ethical and Policy Issues in Data Science has been renamed as Case Studies in Data Science.

The above mentioned additions do not impact currently enrolled students. However, if you haven't already enrolled in Data Science Postgraduate project, from 2019 onwards you will have the choice between Project Stream and Research Stream.

_______________________________________________________________________________________

Credit Transfer and Recognition of Prior Learning (RPL)

At RMIT you can apply for credit so your previous learning or experience counts toward your RMIT program.

Lodge the relevant credit/RPL form(s) on the RMIT Connect Student Portal as soon as possible along with all your supporting documents, e.g. transcript, resume, reference letters etc. to ensure you can enrol the correct courses for the semester.  On the successful outcome of your application, a customised study plan will be issued to you which you must follow.

Note: Non-compliance to your study plan can result in delay of graduation and/or need to take additional courses.

*Top of page


Year One of Program

As not all courses run every semester, the following is the recommended sequence of courses for full-time students (without any advanced standing) commencing in Semester 1:

Semester 1:

  • COSC2670 Practical Data Science
  • COSC2531 Programming Fundamentals
  • ISYS1055 Database Concepts
  • MATH1324 Introduction to Statistics

Semester 2:

  • MATH2349 Data Preprocessing
  • COSC1295 Advanced Programming
  • MATH2270 Data Visualisation
  • COSC2669 Case Studies in Data Science

 

Please ensure that you have met necessary prerequisites by checking course guides - click YES in the Preqs/Coreqs column.

Complete the following Six (6) Courses:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Practical Data Science12YesCOSC2670City Campus1367
Programming Fundamentals12YesCOSC2531City Campus13701371
Database Concepts12YesISYS1055City Campus13391348
Introduction to Statistics12YesMATH1324City Campus1160 (FF)1154 (FF)
Data Preprocessing12YesMATH2349City Campus11401138
Advanced Programming12YesCOSC1295City Campus13161313
AND

Select and Complete Two (2) of the following Courses:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Big Data Processing12YesCOSC2637City Campus1319
Data Visualisation12YesMATH2270City Campus11411139
Case Studies in Data Science12YesCOSC2669City Campus1360
 
AND

*Top of page


Year Two of Program

As not all courses run every semester, the following is the recommended sequence of courses for full-time students.

1. Project Stream:

Semester 1:

  • Four (4) Data Science Program Option Courses

Semester 2:

  • COSC2637 Big Data Processing
  • COSC2667 Data Science Postgraduate Project (24CP)
  • One (1) Data Science Program Option Course

2. Research Stream:

Semester 1:

  • COSC2149 Research Methods
  • Three (3) Data Science Program Option Courses

Semester 2:

  • COSC2179 Minor Thesis (36CP)
  • COSC2637 Big Data Processing

 

Please ensure that you have met necessary prerequisites by checking course guides - click YES in the Preqs/Coreqs column.

{

Select and Complete One (1) of the following Courses that you have not previously completed:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Big Data Processing12YesCOSC2637City Campus1319
Data Visualisation12YesMATH2270City Campus11411139
Case Studies in Data Science12YesCOSC2669City Campus1360
AND

Program Option: Complete the following One (1) Course:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Data Science Postgraduate Project24YesCOSC2667City Campus13371346
AND

Select and Complete Five (5) Courses from Data Science Program Option Courses List (see Option Courses table below):

}
OR
{

Research Option 1: Complete the following Two (2) Courses:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Research Methods12YesCOSC2149City Campus1334
Minor Thesis/Project36YesCOSC2179City Campus13571362
AND

Select and Complete Three (3) Courses from Data Science Program Option Courses List (see Option Courses table below):

}
OR
{

Research Option 2: Complete the following Three (3) Courses:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Research Methods12YesCOSC2149City Campus1334
Minor Thesis/Project Part A24YesCOSC2389City Campus13581363
Minor Thesis/Project Part B12YesCOSC2390City Campus13591364
AND

Select and Complete Three (3) Courses from Data Science Program Option Courses List (see Option Courses table below):

AND

Data Science Program Option Course List:

Course Title

Credit Points

Prereqs/ Coreqs

Course Code

Campus

Semester 1 Class

Semester 2 Class

Algorithms and Analysis12YesCOSC1285City Campus13191316
Artificial Intelligence12YesCOSC1125City Campus1322
Big Data Management12YesCOSC2636City Campus1325
Cloud Computing12YesCOSC2640City Campus1322
Data Mining12YesCOSC2111City Campus1331
Database Systems12YesCOSC2407City Campus1341
Forecasting12YesMATH1307City Campus1143
Web Search Engines and Information Retrieval12YesISYS1078City Campus1352
Mathematical Modelling and Decision Analysis12YesMATH1293City Campus1157
Machine Learning12YesMATH2319City Campus1163
Regression Analysis12YesMATH1312City Campus1178
Social Media and Networks Analytics12YesCOSC2671City Campus1335
Time Series Analysis12YesMATH1318City Campus1208
Usability Engineering12YesCOSC1182City Campus1280
 

*Top of page



Contact details and related links

Program structure enquiries

College of Science, Engineering and Health
Academic Services Centre - Melbourne City Campus

Enquiries can be submitted via RMIT Connect Student Portal

Building 10, Level 9, Room 1
124 La Trobe Street
Melbourne VIC 3000
Tel: +61 3 9925 2621

___________________________________________________________________

Program Manager: Dr. Zhifeng Bao

School of Science

Email: zhifeng.bao@rmit.edu.au

___________________________________________________________________

Canvas Shell for MC267 Program: https://rmit.instructure.com/courses/46004

___________________________________________________________________

Timetabling

Please go to the Class timetables web page to access timetabling information.

 

Material fees

Some courses and programs have material fees (fees for field trips, goods or services) associated with them. In most cases these charges are not compulsory, but are levied by the teaching school for materials they purchase on your behalf for use in your studies. Go to the Material Fees web page to check the material fees for your program and courses.

Enrolment

For more information about enrolment at RMIT University, please go to the Enrolment home page.

*Semester 1 classes generally commence in February and Semester 2 classes generally commence in July. Please contact your school for more information about specific class start days.

Policies

For more information about other RMIT University policies, please go to the Policies web site.

*Top of page