Availabilities:

LocationDomesticInternational
Gold Coast
Melbourne
Online
Term2,5
N/A
Perth
Sydney

Unit description

Introduces students to big data technologies. Students will gain the knowledge and skills to design and implement data analytics models using programming languages and contemporary data analytics tools to solve real-world problems and aid decision-making.

Unit content

  1. Introduction to Big Data Analytics
  2. Data Pre-processing
  3. Data Wrangling
  4. Introduction to Neural Networks
  5. Neural Network based Data Modelling
  6. Big Data Analytics Case study

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:
1use contemporary data analytics libraries and tools
2develop and apply algorithms to prepare data for analysis
3analyse and apply appropriate data modelling approaches
4develop business intelligence systems using data analytics tools and programming libraries

On completion of this unit, students should be able to:

  1. use contemporary data analytics libraries and tools
  2. develop and apply algorithms to prepare data for analysis
  3. analyse and apply appropriate data modelling approaches
  4. develop business intelligence systems using data analytics tools and programming libraries

Prescribed Learning Resources

Prescribed Texts
  • Prescribed text information is not currently available.
Prescribed Resources/Equipment
  • Prescribed resources/equipment information is not currently available.

Prescribed Texts
  • Prescribed text information is not currently available.
Prescribed Resources/Equipment
  • Prescribed resources/equipment information is not currently available.
Prescribed Learning Resources may change in future Teaching Periods

Teaching and assessment

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project40%
Project50%
Practical skills10%

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project40%
Project50%
Practical skills10%

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project40%
Project50%
Practical skills10%

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project40%
Project50%
Practical skills10%

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project40%
Project50%
Practical skills10%
Notice

Intensive offerings may or may not be scheduled in every teaching period. Please refer to the timetable for further details.

Southern Cross University employs different teaching methods within units to provide students with the flexibility to choose the mode of learning that best suits them. SCU academics strive to use the latest approaches and, as a result, the learning modes and materials may change. The most current information regarding a unit will be provided to enrolled students at the beginning of the teaching period.

Fee information

Domestic

Commonwealth Supported courses
For information regarding Student Contribution Amounts please visit the Student Contribution Amounts.

Fee paying courses
For postgraduate or undergraduate full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees

International

Please check the international course and fee list to determine the relevant fees.

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