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

Essential foundations for any machine learning application are a basic statistical analysis of the data to be processed, a solid understanding of the mathematical foundations underpinning machine learning as well as the basic classes of learning/adaptation concepts. Those foundations are bundled in this single, introductory course to machine learning in preparation for deeper explorations into the topic, but also as a standalone unit.

Learning Outcomes

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

  1. Develop an appreciation for what is involved in learning from data.
  2. Understand basic data wrangling and data exploration.
  3. Describe a variety of machine learning tasks: clustering, dimensionality reduction, regression and classification.
  4. Understand how to formalise practical problems in terms of above tasks.
  5. Interpret mathematical equations from linear algebra, calculus, statistics, and probability theory in terms of machine learning methods.
  6. Understand how to perform evaluation of learning algorithms and model selection in practical problems.

Indicative Assessment

  1. Assignments (40) [LO 1,2,3,4,5,6]
  2. Final Exam (60) [LO 1,2,3,4,5,6]

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Up to 60 hours of total face-time, which includes interactions with lectures and tutors. Up to 70 hours of total preparation, repeat, assignment and practical exercise time.

Inherent Requirements


Requisite and Incompatibility

To enrol in this course you must have completed COMP1110 or COMP1140. Incompatible with COMP6670.

Prescribed Texts


Assumed Knowledge

Students are assumed to have taken the highest level of high school mathematics available. For ACT students this means a double major in specialist mathematics. For NSW students this means HSC Maths Extension 2. Other students should have equivalent background knowledge, which can gained through courses such as MATH1013 or MATH 1115.


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
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

There are no current offerings for this course.

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