MIS772 - Predictive Analytics

Unit details

Year:

2024 unit information

Enrolment modes:

Trimester 1: Burwood (Melbourne), Online
Trimester 2: Burwood (Melbourne), Online
Trimester 3: Burwood (Melbourne), Online

Credit point(s):1
EFTSL value:0.125
Unit Chair:Trimester 1: Rens Scheepers
Trimester 2: Arman Kaldi
Trimester 3: Arman Kaldi
Prerequisite:

MIS770 or MIS770A

Corequisite:Nil
Incompatible with: Nil
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 1.5 hour on-campus practical experience (laboratory) each week

Educator-facilitated (scheduled) learning activities - online unit enrolment:

1 x 2 hour recorded lecture provided and 1 x 1.5 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 with ‘Big Data’. Students will be given the opportunity to gain hands-on experience with one of the 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

Explain predictive analytics concepts and techniques. 

GLO1: Discipline-specific knowledge and capabilities

ULO2

Analyse multifaceted real-world business problems, and subsequently propose appropriate analytic solutions using a combination of predictive techniques. 

GLO1: Discipline-specific knowledge and capabilities
GLO5: Problem solving

ULO3

Construct and evaluate integrated predictive analytic solutions using contemporary analysis tools. 

GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy

ULO4

Prepare reports that effectively communicate your solution(s) to business problems.

GLO2: Communication

Assessment

Assessment Description Student output Grading and weighting
(% total mark for unit)
Indicative due week
Assessment 1: (Individual) Case Study: Data analysis with written Report (Business)

Data analysis file plus 500 words 

15% Week 4
Assessment 2: (Individual) Case Study: Data analysis with written Report (Analytical)
 

Data analysis file plus 2500 words 

35% Week 9
End-of-Unit Assessment: Written 2 hours 50% 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: MIS772 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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