• Offered by School of Computing
  • ANU College ANU College of Engineering Computing & Cybernetics
  • Course subject Computer Science
  • Areas of interest Statistics, Computer Science, Information Technology, Algorithms and Data
  • Academic career UGRD
  • Mode of delivery Online or In Person
  • Co-taught Course
  • STEM Course

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

Other Information

Indicative Assessment

  1. Assignments (30) [LO null]
  2. Labs & Quizzes (20) [LO null]
  3. Final Exam (50) [LO null]

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

Inherent Requirements


Requisite and Incompatibility

To enrol in this course, you must have completed COMP1100 or COMP1130. Incompatible with COMP6420

Prescribed Texts



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

Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees

Student Contribution Band:
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

6.00 0.12500
Domestic fee paying students
Year Fee
2024 $4980
International fee paying students
Year Fee
2024 $6360
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

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There are no current offerings for this course.

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