UO Big Data Analytics
Undergraduate
INFS 2039
Undergraduate
100% online
164143
4.5
Yes
10 weeks
View fees for this course
This course has not been
timetabled for 2018.
Course aim
To provide an overview of the tools and techniques of data analytics for big data, and how these can be used by an organisation. Tto introduce and use some of the common big data tools.
Course content
An overview of big data analytics: data analytics lifecycle; Clustering; association rules; regression; classification; time series analysis; text analytics; MapReduce and Hadoop; In-Database analytics.
Big Data: Analytics flow for Big Data; MapReduce; NoSQL; data acquisition and storage.
Batch Analytics: Map-Reduce and Hadoop; Pig; Oozie, Spark.
Real-Time Analytics: Storm; Spark.
Interactive Querying, serving databases and Web Frameworks.
Textbooks
Bahga, A, Madisetti, V 2016, Data Science and Analytics: A hands on Approach, Arshdeep Bahga & Vijay Madisetti
Prerequisites
Nil
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)
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Fee-paying program for domestic and international students
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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