UO Big Data in the Cloud
Undergraduate
INFS 3088
Undergraduate
100% online
171491
4.5
Yes
10 weeks
View fees for this course
This course has not been
timetabled for 2021.
Course aim
To interoperate with cloud based information systems in order to extract meaningful data for analysis and publish visualisations.
Course content
Topics covered in this course include: overview of big data analytics; characteristics of big data; analysis flow for big data; big data manipulation techniques: batch analytics (Hadoop Map-Reduce), real-time analytics, interactive querying; big data languages/tools: Pig, Oozie, Spark, Strom, Hive; big data search: Solr, Elasticsearch; big data applications (e.g. recommendation systems, time series analysis, text analytics); and web framework: Django.
Textbooks
Nil
Prerequisites
Subject Area & Catalogue Number | Course Name |
---|---|
Group 1
Alternatively, students must have completed the following courses: |
|
INFS 3081 | UO Predictive Analytics |
INFS 3079 | UO Business Analytics |
Common to all relevant programs | |
---|---|
Subject Area & Catalogue Number | Course Name |
INFT 2066 | UO Cloud Platforms |
COMP 2033 | UO Data Structures |
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
Continuous assessment, Examination
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