Operations Analysis
COURSE INFORMATION
DATES AVAILABLE
Study Period 5 2025 (July – November 2025)
Please note there are limited places available for this short course, admittance will be granted as applications are received.
CONTACT HOURS
This course runs over 10 weeks, with 5 x 2-hour tutorials during that time.
MODE
100% online
ENTRY REQUIREMENTS
None
FEES
Costs for the short course, vary per participant depending on the number:
- 1-2: $3,850.00 (per participant)
- 3-4: $3,300.00 (per participant)
- 5+: $2,750.00 (per participant)
LOCATION
100% Online
Course overview
The Professional Certificate in Operations Analysis is designed for domain experts transitioning into operations analysis roles. It equips participants with foundational skills in computational programming, systems thinking, data analysis, quantitative methods, and complex problem-solving. The course focuses on a wide range of topics, providing participants with the tools to understand, communicate, and apply operations analysis techniques in their professional contexts.
Course structure
Operations Analysis contains five modules structured to build participant knowledge and skills as they progress
through the course.
- Module 1. Introduction to Systems Thinking: In this module, students will learn about framing an operational problem using systems thinking principles. Topics in this module include problem framing, systems dynamics, gap analysis, and systems optimisation.
- Module 2. Foundational Computational Programming: In this module, students will learn about writing and debugging scripts for data processing. Topics in this module include an introduction to several programming languages and computational tools such as MATLAB/GNU Octave, Excel, VBA and SQL. The module also discusses the principles of scripting and building relational databases.
- Module 3. Data Analysis and Visualization: In this module, students will learn about creating data visualisations to support hypothetical decision-making scenarios. Topics in this module include fundamentals of data modelling, data visualisation and quantitative/qualitative data representation methods.
- Module 4. Quantitative Analysis Techniques: By completing this module, students will be able to apply statistical methods to analyse system performance data. Topics in this module include an introduction to probability theory and statistics, Bayesian and regression analysis, and Monte Carlo Simulation.
- Module 5. Complex and Wicked Problem Solving: By completing this module, students will be able to develop strategic approaches to deal with multifaceted complex problems using techniques such as risk management, and root cause analysis. They will also learn about various types of modelling and simulation techniques to help them with these, such as agent-based, discrete event, and spatial modelling.
Assessment
Assessment will consist of written reflection, assessments, tests/quizes and reports throughout the 10 weeks.
How to apply
Please complete the application form below and return the completed form to STEM-TeachingLearning@unisa.edu.au.
Additional information
Cancellation policy
The University of South Australia reserves the right to cancel events and issue refunds. In the event that an attendee cannot attend, a substitute is welcome to attend in their place. No refunds will be given unless 21 days notice is given in writing prior to the date of the planned event. If less than 21 days the fee can be used for the same course at a later stage, or another course of the same value.
