MIS772 - Predictive Analytics

Unit details

Year

2026 unit information

Enrolment modes:

Trimester 1: Burwood (Melbourne), Online
Trimester 2: Burwood (Melbourne), Online
Trimester 3: Burwood (Melbourne), Online, GIFT City (India)^

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

For S735A students: MIS770 or SIT718

For all other students: MIS770

Corequisite:Nil
Incompatible with: Nil
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

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.

Note:

^GIFT City (India) offering is available to students enrolled at the GIFT City (India) campus only.

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.

Learning outcomes

ULO These are the Unit Learning Outcomes (ULOs) for this unit. At the completion of this unit, successful students can:

Alignment to Deakin Graduate Learning Outcomes (GLOs)

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

 

Communicate business solutions effectively to relevant audience. 

GLO2: Communication

Assessment

Assessment Description Student output Grading and weighting
(% total mark for unit)
Indicative due week
Assessment 1: (Individual) Report (Analytical) 

Data analysis file plus 1500 words

30% Week 4
Assessment 2: (Individual) Report (Business) 

Data analysis file plus 2500 words

35% Week 8
Assessment 3: (Individual) Live Oral Assessment  20 minutes 35% End-of-unit assessment and exam 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 Assessment 3 to evidence a minimum proficiency in the aligned discipline learning outcomes included in this unit.

Learning resource

The texts and reading list for MIS772 can be found via the University Library.

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.

Bring Your Own Device (BYOD)

To fully engage with Deakin's learning experiences, students must be able to access and use internet-connected devices as outlined in computing requirements at Deakin.

To support student success at Deakin, we have a bring-your-own-device (BYOD) learning environment that acknowledges that students and educators bring with them the digital tools they regularly use to complete academic tasks. These tools stay with you beyond the classroom, helping you to keep learning, explore ideas more deeply, and connect with knowledge in ways that matter to you.

Students requiring a loan device should visit our Loan Laptop webpage or students requiring longer-term assistance should visit our Student Financial Assistance webpage.

Unit Fee Information

Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study and their study discipline, and your study load.

Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.

Estimate your fees

For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current Students website.