Machine Learning Fundamentals | Study in Queenstown, NZ

Level 5
16 Weeks
queenstown
Intakes in April, August

There is an acute worldwide shortage of machine learning experts and intense international competition for talent. Machine learning is the highest demand growth tech skillset globally

This Certificate in Machine Learning Fundamentals will take students with no prior experience to a stage where they have the skills to be industry-ready upon graduation.

Machine Learning (ML) is the process of building, and using, predictive models. Artificial Intelligence (AI) is the software that surrounds these predictive models while in use, allowing software applications to become more accurate at predicting outcomes.

The qualification will focus on the foundations of machine learning including:

Types of machine learning algorithms including supervised and unsupervised learning
Regression and Classification techniques for machine learning applications
Using existing machine learning libraries to generate predictions
Constructing and documenting datasets
Understanding and applying Responsible AI and business ethics to machine learning systems
Applying and improving deep learning systems

Who is this course for?

School leavers – high school students interested in technology
University students / Up Skillers – those looking to add to their skillset
Career changers – those wanting to get into a new industry

Programme at a glance

16 Weeks | Level 5 | Credits: 60

Qualification: Certificate in Machine Learning Fundamentals (Level 5) (Micro-credential)

Delivered at our: Queenstown Campus

This Certificate is made up of three micro-credentials: Machine Learning Fundamentals, Responsible AI and Machine Learning Team Project

Machine Learning Fundamentals | 40 Credits.

Course Content:

Introduction to Machine Learning
Predicting Unknown Values with Machine Learning Models
Constructing and documenting datasets
Responsible AI and Business Ethics
Introduction to Deep Learning

Responsible AI | 10 Credits.

Course Content:

The components of Responsible AI that are relevant to contemporary scenarios
Distinguishing uses and end users of AI systems
Using ethics to inspect aspects of datasets
Comparing the different roles that are responsible and accountable for an AI system
An ethical evaluation of an AI system

Machine Learning Team Project | 10 Credits.

Course Content:

Understanding the relationship of Machine Learning with Responsible AI and business ethics
Collaborating, problem solving, and communicating in teams to improve machine learning systems
Presenting findings and results of machine learning systems to internal stakeholders

Entry Requirements

To be eligible for entry, applicants must meet the following requirements:

Be at least 17 years of age at course commencement
All applicants will require a pre-course discussion with the Academic Director to align suitability
International Students: IELTS score of at least 5.5 with no band score lower than 5.0 or equivalent

Pathways into Industry

QRC aligns learning and training directly to that of industry needs and requirements which provides a valued outcome for learners.

Entering into Industry: Aligning supply & demand

This micro credential is in response to a united industry voice that is facing demand for entry level machine learning operators for current and
future work streams across key businesses both domestically and globally.

The focus is on developing a tech eco system in which entry level machine learning operators can understand and apply the fundamentals of machine learning to solve business tasks.

However, “a lack of people skills” has been identified as a problem within the industry. For machine learning and AI employers, “soft skills are seen as very important to critically important”, especially in client-facing industries. These soft skills facilitate responsible AI, as they promote empathy and understanding others lived experiences.

This qualification teaches the necessary machine learning and AI skills, along with the equally important soft skills.

2023 Fees

*All fees are in NZD$ | Fees are subject to change
2023 Domestic Tuition Fees
Certificate in Machine Learning Fundamentals (60 Credits)	$3,200

*All fees are in NZD$ | Fees are subject to change
2023 International Tuition Fees	International
Certificate in Machine Learning Fundamentals (60 Credits)	$9,000

Dates
November 2022	21st November - 16th December 2022 17th December 2022 - 8th January 2023 Christmas Break 9th January - 17th February 2023 20th February - 24th February 2023 - Recess 27th February - 6th April 2023
April 2023	11th April - 16th June 2023 19th June - 23rd June 2023 Recess 26th June - 4th August
August 2023	21st August - 27th October 2023 30th October - 3rd November 2023 Recess 6th November - 15th December 2023

Find out more:

In the News

Supervised vs Unsupervised Learning:

Broadly speaking, you can put most machine learning algorithms into one of two categories – supervised vs unsupervised. If you realise that you need to use machine learning to solve a problem, you will need to determine what kind of method you will use.

Finding the dream job:

Machine Learning is technology that lets a computer get smarter and smarter all by itself just by looking at data.

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