UO Predictive Analytics
Undergraduate
INFS 3081
Undergraduate
100% online
164145
4.5
Yes
10 weeks
View fees for this course
This course has not been
timetabled for 2018.
Course aim
To enable students to perform, on large data sets, data exploration, visualisation, and preliminary analysis using predictive modelling techniques.
Course content
Data exploration, visualisation and preliminary analysis: advanced exploratory data analysts; data visualisation; data quality verification; missing data analysis; data manipulation and cleaning.
Predictive modelling: logistic regression and generalised linear models; decision trees; random forests; generalised boosted models; naive Bayes classifiers and other techniques.
Textbooks
Tan, P; Steinbach, M; Kumar, V 2013, Introduction to Data Mining: Pearson New International Edition, Pearson
Prerequisites
Common to all relevant programs | |
---|---|
Subject Area & Catalogue Number | Course Name |
INFS 3079 | UO Business Analytics |
INFS 3080 | UO Data Visualisation |
Corequisite(s)
Nil
Teaching Method
Component | Duration | ||
---|---|---|---|
EXTERNAL, ONLINE ACTIVITY | |||
Online | 10 weeks x N/A |
Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.
Assessment
Assignment, Continuous assessment
Fees
EFTSL*: 0.125
Commonwealth Supported program (Band 2)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.
Non-award enrolment
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* Equivalent Full Time Study Load. Please note all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation