MIS772 - Predictive Analytics
Unit details
Year: | 2021 unit information |
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Important Update: | Unit delivery will continue to be provided in line with the most current COVIDSafe health guidelines. This may include a mix of on-campus and online activities. To find out how you are impacted, please check your unit sites for announcements and updates. Unit sites open one week prior to the start of each Trimester/Semester. Thank you for your flexibility and commitment to studying with Deakin in 2021. Last updated: 4 June 2021 |
Enrolment modes: | Trimester 1: Burwood (Melbourne), Online Trimester 2: Burwood (Melbourne), Online |
Credit point(s): | 1 |
EFTSL value: | 0.125 |
Unit Chair: | Trimester 2: Quan Vu Trimester 1: Rens Scheepers |
Prerequisite: | MIS770 or MIS770A* for M722, M751, M761, M661, M755 and S777 students ONLY |
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. |
Scheduled learning activities - campus: | 1 x 2 hour class, 1 x 1 hour computer lab per week |
Scheduled learning activities - cloud: | 11 x 2 hour class (livestreamed with recordings provided) + 11 x 1 hour online seminar/workshop |
Note:*Students who are either enrolled in or have completed MIS770A - please contact a student adviser buslaw@deakin.edu.au |
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 |
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ULO1 | Explain and critique major statistical theories and data mining concepts. | GLO1: Discipline-specific knowledge and capabilities |
ULO2 | Critically evaluate and build predictive analytics solutions for real-world requirements. | GLO1: Discipline-specific knowledge and capabilities |
ULO3 | Analyse multifaceted business problems, and subsequently propose, construct and evaluate analytic solutions using a combination of predictive techniques and methods. | GLO1: Discipline-specific knowledge and capabilities |
These Unit Learning Outcomes are applicable for all teaching periods throughout the year
Assessment
Assessment Description | Student output | Grading and weighting (% total mark for unit) | Indicative due week |
Assessment 1 (Individual) - Develop predictive models for a business | 2000 words | 20% | Week 5 |
Assessment 2 (Individual) - Develop advanced predictive models for a business | 3000 words | 30% | Week 9 |
Examination | 2 hours | 50% | 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 the examination
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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