MIS272 - Predictive Analytics
Unit details
| Year: | 2024 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Burwood (Melbourne), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Previously coded as: | MIS372 |
| Unit Chair: | Trimester 2: Rens Scheepers |
| Prerequisite: | MIS171 |
| Corequisite: | Nil |
| Incompatible with: | MIS372, MIS772 |
| Typical study commitment: | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Educator-facilitated (scheduled) learning activities - on-campus unit enrolment: | 1 x 2 hour on-campus (livestreamed) lecture (recordings provided) and 1 x 1 hour on-campus seminar each week |
| Educator-facilitated (scheduled) learning activities - online unit enrolment: | 1 x 2 hour recorded lecture provided and 1 x 1 hour online seminar (recordings provided) each week |
Content
The ‘information age’ has combined with the widespread adoption of digital technology to turn information into a key business asset. Businesses and governments now have access to massive volumes of data and require skills and expertise in making sense of this information for strategic decision making. This unit will provide students with the knowledge and skills to build predictive models and use data mining tools in real business scenarios. Students will be given the opportunity to gain hands-on experience with most widely used predictive analytics software tools globally.
| ULO | These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: | Deakin Graduate Learning Outcomes |
|---|---|---|
| ULO1 | Apply key statistical theories and data mining concepts to selected business scenarios. | GLO1: Discipline-specific knowledge and capabilities |
| ULO2 | Build predictive analytics models in real-world situations. | GLO1: Discipline-specific knowledge and capabilities |
| ULO3 | Apply current techniques and trends in predictive analytics to the business environment. | GLO1: Discipline-specific knowledge and capabilities |
Assessment
| Assessment Description | Student output | Grading and weighting (% total mark for unit) | Indicative due week |
|---|---|---|---|
| Assessment 1: (Individual) Report (Business) | 600 words | 20% | Week 5 |
| Assessment 2: (Individual) Report (Business) | 1400 words | 40% | Week 9 |
| End-of-unit assessment task: Written | 2 hours | 40% | End-of-unit assessment period |
The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.
Hurdle requirement
Hurdle requirement: Achieve at least 50% of the marks available on the end-of-unit assessment to evidence a minimum proficiency in the aligned discipline learning outcomes included in this unit.
Learning Resource
The texts and reading list for the unit can be found on the University Library via the link below: MIS272 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.
Unit Fee Information
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