• Offered by Research School of Computer Science
  • ANU College ANU College of Engineering and Computer Science
  • Course subject Computer Science
  • Academic career UGRD
  • Course convener
    • Dr Ramesh Sankaranarayana
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2020
    See Future Offerings

Commerce and research are being transformed by data-driven discovery and prediction.  Skills required for data analytics at massive levels – scalable data management on and off the cloud, parallel algorithms, statistical modeling, and proficiency with a complex ecosystem of tools and platforms – span a variety of disciplines and are not easy to obtain through conventional curricula. Tour the basic techniques of data science, including both SQL and NoSQL solutions for massive data management, basic statistical modeling (e.g., descriptive statistics, linear and non-linear regression), algorithms for machine learning and optimization, and fundamentals of knowledge representation and search.  Learn key concepts in security and the use of cryptographic techniques in securing data.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Demonstrate a conceptual understanding of database systems and architecture, data models and declarative query languages
  2. Define, query and manipulate a relational database
  3. Demonstrate basic knowledge and understanding of descriptive and predictive data analysis methods, optimization and search, and knowledge representation.
  4. Formulate and extract descriptive and predictive statistics from data
  5. Analyse and interpret results from descriptive and predictive data analysis
  6. Apply their knowledge to a given problem domain and articulate potential data analysis problems
  7. Identify potential pitfalls, and social and ethical implications of data science
  8. Explain key security concepts and the use of cryptographic techniques, digital signatures and PKI in security

Indicative Assessment

  1. Assignments (30) [LO null]
  2. Labs (5) [LO null]
  3. Mid-semester exam (15) [LO null]
  4. Final Exam (50) [LO null]

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Workload

Up to 36 one-hour lectures and eight two-hour labs.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course, you must have completed COMP1100 or COMP1130

Prescribed Texts

None

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:
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
Domestic fee paying students
Year Fee
2020 $4320
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3296 24 Feb 2020 02 Mar 2020 31 Mar 2020 29 May 2020 In Person N/A

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