UO Advanced Topics in Data Analytics
Course Level Undergraduate
Area/Catalogue
INFS 3087
Course Level
Undergraduate
Study Method
100% online
Course ID
171435
Unit Value
4.5
UniSA Online Elective Course
Yes
Duration
10 weeks
Fees
View fees for this course
Course aim
This course aims to extend the knowledge and skills in applying a range of advanced data analytics techniques and integrate responsibility into the systems they design, build and deploy.
Course content
Topics covered in this course include responsible data analytics, time series analysis, reinforcement learning, deep neural networks and computer vision, and natural language processing.
Textbooks
Nil
Prerequisites
| Common to all relevant programs | |
|---|---|
| Subject Area & Catalogue Number | Course Name |
| INFT 3046 | UO Machine Learning |
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
Case study
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
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.
* 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
Online Course Facilitators
