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Agile Decision Making in a Digital World (MGMT90267)
Graduate courseworkPoints: 12.5Online
Please refer to the return to campus page for more information on these delivery modes and students who can enrol in each mode based on their location.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Term 3
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Contact hours: https://unimelb.edu.au/professional-development/contact-us
Dr Zahra Hosseinifard zahra.h@unimelb.edu.au
Dr Michal Carrington michal.carrington@unimelb.edu.au
Overview
Availability | Term 3 - Online |
---|---|
Fees | Look up fees |
The expectations on contemporary managers to make agile decisions in complex digitised environments are increasing. This subject focuses on the development of managerial capabilities to engage appropriate decision-making models and employ new-generation analytic tools that best-fit the scenario as it unfolds.
This subject provides both conceptual frameworks and practical illustrations of quantitative decision-making techniques including decision trees and optimisation to tackle business problems. Students will be shown how to use these quantitative approaches to analyse business problems and, based on these analyses, make effective decisions. These frameworks can be applied to various decisions faced by organisations, with applications in different areas such as operations, marketing, financial and nursing management.
Managers must also decide if and how to employ Artificial Intelligence (AI) within their workplace decision making to create value for the organisation. This subject explores the function, advantages and limitations of AI and machine learning, and how these tools can optimise decision making in complex digitised environments. Key topics include: (1) the foundations of AI—inputs, processes, and outputs; (2) AI in action in various contexts to evaluate the opportunities and challenges; and (3) the critical analysis of AI to illustrate contrasting scenarios in which the adoption of AI creates value and destroys value for the organisation.
Intended learning outcomes
On completion of this subject, students should be able to:
- Understand the fundamentals of decision making for business problems and application of quantitative approaches to management.
- Formulate various business optimisation problems as mathematical models, such as linear programming and integer programming and decision tree.
- Understand the function and processes of Artificial Intelligence (AI) to aid decision making in complex business environments.
- Critically evaluate the opportunities and limitations of adopting AI to create value for the organisation.
Generic skills
- Become skilled at analysing business decision problems, building analytics models and solving these to gain managerial insights
- Critical thinking in relation to the effectiveness of solutions and managerial decision analysis
- Application of theory to practice in the field of management science
Last updated: 9 April 2024
Eligibility and requirements
Prerequisites
None
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 9 April 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Written activity
| Week 1 | 10% |
Written activity
| Week 4 | 10% |
Report
| Week 5 | 30% |
Quiz
| Week 7 | 20% |
Report
| Due during the assessment period | 30% |
Last updated: 9 April 2024
Dates & times
- Term 3 - Online
Principal coordinator Zahra Hosseinifard Mode of delivery Online Contact hours 24 hours of online contact; 56 hours of case study analysis; 20 hours of online forum discussion activity; 70 hours of online activities, participation in simulations, and other management related analyses. Total time commitment 170 hours Pre teaching start date 12 July 2021 Pre teaching requirements During the pre-teaching period, students should familiarise themselves with the learning platform and the subject requirements. Teaching period 19 July 2021 to 12 September 2021 Last self-enrol date 13 July 2021 Census date 6 August 2021 Last date to withdraw without fail 27 August 2021 Assessment period ends 19 September 2021 Term 3 contact information
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Contact hours: https://unimelb.edu.au/professional-development/contact-us
Dr Zahra Hosseinifard zahra.h@unimelb.edu.au
Dr Michal Carrington michal.carrington@unimelb.edu.au
Last updated: 9 April 2024
Further information
- Texts
Prescribed texts
There are no specifically prescribed or recommended texts for this subject.
Last updated: 9 April 2024