Methods in Machine Learning

Course code Qualifications are made up of courses. Some universities call these papers. Each course is numbered using six digits.: 159224
Level The fourth number of the course code shows the level of the course. For example, in course 219206, the fourth number is a 2, so it is a 200-level course (usually studied in the second year of full-time study).: 200-level
Credits Each course is worth a number of credits. You combine courses (credits) to meet the total number of credits needed for your qualification.: 15
Subject: Computer Science

Course planning information

Complete first

You need to complete the above course or courses before moving onto this one.

You must complete at least 45 credits from 100-level before enrolling in 200-level courses.

1 Describe and explain the core concepts of machine learning methods and techniques.
2 Implement and apply machine learning algorithms to specified problems.
3 Compare and evaluate training methods for different application areas.
4 Utilise modern machine learning tools for practical applications.
5 Discuss relevant ethical, legal and cultural considerations (including Māori and Indigenous contexts) related to artificial intelligence and machine learning.

Learning outcomes can change before the start of the semester you are studying the course in.

Assessment weightings can change up to the start of the semester the course is delivered in.

You may need to take more assessments depending on where, how, and when you choose to take this course.

Explanation of assessment types

Computer programmes: Computer animation and screening, design, programming, models and other computer work.
Creative compositions: Animations, films, models, textiles, websites, and other compositions.
Exam College or GRS-based (not centrally scheduled): An exam scheduled by a college or the Graduate Research School (GRS). The exam could be online, oral, field, practical skills, written exams or another format.
Exam (centrally scheduled): An exam scheduled by Assessment Services (centrally) – you’ll usually be told when and where the exam is through the student portal.
Oral or performance or presentation: Debates, demonstrations, exhibitions, interviews, oral proposals, role play, speech and other performances or presentations.
Participation: You may be assessed on your participation in activities such as online fora, laboratories, debates, tutorials, exercises, seminars, and so on.
Portfolio: Creative, learning, online, narrative, photographic, written, and other portfolios.
Practical or placement: Field trips, field work, placements, seminars, workshops, voluntary work, and other activities.
Simulation: Technology-based or experience-based simulations.
Test: Laboratory, online, multi-choice, short answer, spoken, and other tests – arranged by the school.
Written assignment: Essays, group or individual projects, proposals, reports, reviews, writing exercises, and other written assignments.

There are no set texts for this course.