• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Areas of interest Computer Science, Advanced Computing, Information-Intensive Computing, Algorithms and Data
  • Academic career Undergraduate
  • Course convener
    • Dr Ramesh Sankaranarayana
  • Mode of delivery In Person
  • Co-taught Course COMP8430
  • Offered in Second Semester 2018
    See Future Offerings

Real-world data are commonly messy, distributed, and heterogeneous. This course introduces core concepts of data cleaning, standardisation, and data integration, that are aimed at converting and mapping raw data into other formats that allow more efficient and convenient use and analysis of data. The courses also discusses data quality, management, and storage issues as relevant to data analytics.

Learning Outcomes

Upon successful completion of this course, students will:
  1. Critically reflect upon different data sources, types, formats and structures,
  2. Justify and apply data cleaning, preprocessing, and standardisation for data analytics,
  3. Apply data integration concepts and techniques to heterogeneous and distributed data,
  4. Interpret, assess and discuss data quality measurements,
  5. Understand and be able to use advanced data wrangling, data integration, and database techniques as relevant to data analytics.

Indicative Assessment

  1. Written and practical assignments (30% each)
  2. Oral presentation and report (20%)
  3. Final examination (50%)

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

The workload for the course is around 130 hours, including reading, the viewing of online course material, participation in face-to-face lectures, practical labs and tutorials, and preparation for assessments

Requisite and Incompatibility

Students are required to have completed introductory courses on databases, programming, algorithms and statistics (6 units from COMP1030 or COMP1100 or COMP1130 or COMP1730; and 6 units from COMP1040 or COMP1110 or COMP1140).

Indicative Reading List

 A set of readings will be provided at the start of the course

Majors

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
Band 2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings and Dates

The list of offerings for future years is indicative only

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery
9396 23 Jul 2018 30 Jul 2018 31 Aug 2018 26 Oct 2018 In Person

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