Graduate Diploma in Statistics and Operations Research
Royal Melbourne Institute of Technology
About
The Graduate Diploma in Statistics and Operations Research program aims to provide opportunities to further your understanding in the modelling of physical, biological and economic phenomena so that you will be able to contribute to development in industry and commerce.The program furthers your knowledge of statistical and operations research methodologies and provides a theoretical foundation combined with practical applications of current techniques employed by practising engineers, scientists and other professionals in industry, research, consulting, teaching and business.
You will also develop your practical skills in Data Wrangling (MATH2349) which includes a Work Integrated Learning (WIL) experience in which your knowledge and skills are applied and assessed in a simulated workplace context and where feedback from industry and/or community is integral to your experience.GD120P12 Graduate Diploma in Statistics and Operations Research program is an EXIT ONLY award from MC004 Master of Statistics and Operations Research.This program is delivered on campus;
some courses may be available online.
Structure
Year One of Program
Complete the following Four (4) Courses:
| Course Title | Credit Points | Course Code | Campus |
|---|---|---|---|
| Mathematical Modelling and Decision Analysis | 12 | MATH1293 | City Campus |
| Data Wrangling | 12 | MATH2349 | City Campus |
| Applied Analytics | 12 | MATH1324 | City Campus |
| Database Concepts | 12 | ISYS1055 | City Campus |
Select and Complete Two (2) of the following Courses:
| Course Title | Credit Points | Course Code | Campus |
|---|---|---|---|
| Essential Mathematics | 12 | MATH2267 | City Campus |
| Data Visualisation and Communication | 12 | MATH2270 | City Campus |
| Applied Bayesian Statistics | 12 | MATH2269 | City Campus |
| Analysis of Categorical Data | 12 | MATH1298 | City Campus |
| Design and Analysis of Experiments | 12 | MATH1302 | City Campus |
| Forecasting | 12 | MATH1307 | City Campus |
| Multivariate Analysis Techniques | 12 | MATH1309 | City Campus |
| Regression Analysis | 12 | MATH1312 | City Campus |
| Statistical Inference | 12 | MATH1315 | City Campus |
| Statistics of Quality Control and Performance Analysis | 12 | MATH1316 | City Campus |
| Stochastic Processes and Applications | 12 | MATH1317 | City Campus |
| Time Series Analysis | 12 | MATH1318 | City Campus |
| Game Theory and its Applications | 12 | MATH1320 | City Campus |
| Methods and Models of Operations Research | 12 | MATH1326 | City Campus |
| Questionnaire and Research Design | 12 | MATH2218 | City Campus |
| Systems Simulation | 12 | MATH2219 | City Campus |
| System Dynamics | 12 | MATH2220 | City Campus |
| Sports Analytics | 12 | MATH2223 | City Campus |
| Machine Learning | 12 | MATH2319 | City Campus |
| Introduction to Statistical Computing | 12 | MATH1322 | City Campus |
Select and Complete Two (2) of the following Courses:
| Course Title | Credit Points | Course Code | Campus |
|---|---|---|---|
| Scripting Language Programming | 12 | COSC1092 | City Campus |
| Artificial Intelligence | 12 | COSC1125 | City Campus |
| Intelligent Web Systems | 12 | COSC1165 | City Campus |
| Programming Techniques | 12 | COSC1283 | City Campus |
| Algorithms and Analysis | 12 | COSC1285 | City Campus |
| Advanced Programming | 12 | COSC1295 | City Campus |
| Data Mining | 12 | COSC2111 | City Campus |
| Advanced Programming Techniques | 12 | COSC2207 | City Campus |
| Database Systems | 12 | COSC2407 | City Campus |
| Programming Fundamentals | 12 | COSC2531 | City Campus |
| Big Data Management | 12 | COSC2636 | City Campus |
| Big Data Processing | 12 | COSC2637 | City Campus |
| Case Studies in Data Science | 12 | COSC2669 | City Campus |
| Practical Data Science with Python | 12 | COSC2670 | City Campus |
| Social Media and Networks Analytics | 12 | COSC2671 | City Campus |
| GIS Fundamentals | 12 | GEOM1159 | City Campus |
| GIS Principles | 12 | GEOM1163 | City Campus |
| Advanced GIS | 12 | GEOM2151 | City Campus |
| GIS Analytics | 12 | GEOM2152 | City Campus |
| Introduction to Information Security | 12 | INTE1120 | City Campus |
| Case Studies in Cyber Security | 12 | INTE1122 | City Campus |
| Information Theory for Secure Communications | 12 | INTE1128 | City Campus |
| Information Systems Risk Management | 12 | INTE2396 | City Campus |
| Knowledge and Data Warehousing | 12 | ISYS1072 | City Campus |
| Web Search Engines and Information Retrieval | 12 | ISYS1078 | City Campus |
| Data Visualisation and Communication | 12 | MATH2270 | City Campus |
| Applied Bayesian Statistics | 12 | MATH2269 | City Campus |
| Analysis of Categorical Data | 12 | MATH1298 | City Campus |
| Design and Analysis of Experiments | 12 | MATH1302 | City Campus |
| Forecasting | 12 | MATH1307 | City Campus |
| Multivariate Analysis Techniques | 12 | MATH1309 | City Campus |
| Regression Analysis | 12 | MATH1312 | City Campus |
| Statistical Inference | 12 | MATH1315 | City Campus |
| Statistics of Quality Control and Performance Analysis | 12 | MATH1316 | City Campus |
| Stochastic Processes and Applications | 12 | MATH1317 | City Campus |
| Time Series Analysis | 12 | MATH1318 | City Campus |
| Game Theory and its Applications | 12 | MATH1320 | City Campus |
| Methods and Models of Operations Research | 12 | MATH1326 | City Campus |
| Questionnaire and Research Design | 12 | MATH2218 | City Campus |
| Systems Simulation | 12 | MATH2219 | City Campus |
| System Dynamics | 12 | MATH2220 | City Campus |
| Sports Analytics | 12 | MATH2223 | City Campus |
| Machine Learning | 12 | MATH2319 | City Campus |
| Introduction to Statistical Computing | 12 | MATH1322 | City Campus |
Entry requirements
Entry to this program is via MC004 Master of Statistics and Operations Research.
Students in the Masters degree who wish to exit the Masters before completion, may be eligible to take out the intermediary award of GD120 Graduate Diploma in Statistics and Operations Research.
Learning outcomes
The program has a student-focused approach that aims at developing your skills in the use of statistics and operations research in solving real world problems that arise in industry and business environments. This is achieved using statistical software accompanied by an in-depth understanding of the statistical processes involved. By completing this program, you will be particularly knowledgeable, creative and critical in the sense of how you interpret and analyse data. You will also be equipped with the ability to apply knowledge to solve a wide range of real world problems.
Please note that the following list of PLOs applies to MC004 Masters of Statistics and Operations Research. Students exiting MC004 with the Graduate Diploma award will have developed knowldge, skills and their application in areas identified below but not at an AQF 9 program level. Importantly they will not have completed a significant research capstone experience.
The following are the key capabilities developed in the MC004 Masters level program which will make you, as a graduate, relevant to current industry and business requirements:
Personal and professional awareness
- the ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
- the ability to reflect on experience and improve your own future practice
- the ability to apply the principles of lifelong learning to any new challenge.
Knowledge and technical competence
- an understanding of appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.
Problem-solving
- the ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
- an understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.
Communication
- the ability to effectively communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral), and to tailor the style and means of communication to different audiences. Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.
Information literacy
- the ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.
Institution
