Expanding Opportunity with Technology.
There is an acute worldwide shortage of machine learning experts and intense international competition for talent. Machine learning is the highest demand growth tech skill-set globally.
- This programme is designed to create industry ready graduates
- Students with no prior experience in machine learning will have the skills to enter the tech workforce
- Intakes for August 2023 are open now
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.
For more information about the course: Machine Learning Fundamentals
What is Machine Learning?
Find out more about all things Machine Learning, technology in Queenstown and other tech articles. Whether you want to learn how to prep data, explore career opportunities, find new algorithms or use machine learning in your everyday life – you can find all that and more on our news page.
Qualification at a glance
Machine Learning with QRC:
📍 Delivered from our Queenstown campus
📜 Certificate in Machine Learning Fundamentals (Level 5, 60 Credits)
📅 16 Weeks
The number of Machine Learning engineers has increased tenfold in the past five years. Machine Learning qualifications providing introductory concepts, and practical skills necessary to support and develop ML in various industries will be an essential part of IT services in the future.
💻 Employment Pathway
Graduates of the Certificate will be able to apply the fundamentals of Machine Learning to entry level roles in the New Zealand tech, corporate and Health and Education sectors as:
- Entry-level Data Analysts
- Entry-level Business Intelligence Analysts
- Entry-level Machine Learning Engineer
👨🏼🎓 Study Pathway
Upon completion of this certificate learners will have gained the necessary skills and knowledge to proceed into further training in machine learning and further study in data science, data engineering, and software development.
TAUGHT CONTENT | |
---|---|
Module 1 | Introduction to Machine Learning |
Module 2 | Predicting Unknown Values with Machine Learning Models |
Module 3 | Constructing and documenting datasets |
Module 4 | Responsible AI and Business Ethics |
Module 5 | Introduction to Deep Learning |
LEARNING OUTCOMES |
---|
Discuss the difference between supervised and unsupervised learning. |
Distinguish between classification and regression in machine learning |
Use machine learning libraries to predict independent variables. |
Present performance results of a machine learning model. |
Construct and document a data set from raw data. |
Describe and present the importance of implementing responsible AI systems that impact Māori and Pasifika communities. |
Identify how to correct an imbalance in a dataset applying business ethics. |
Select and justify a machine learning model to solve a classification task. |
Apply deep learning models to generate predictions for tabular data. |
Select and adjust hyperparameters for deep learning models to improve performance. |
✔ Suitable for school leavers, career changers, up–skillers already in the business sector who want to expand their knowledge and skills in machine learning to meet the need for entry level tech operators
✔ Applicants must be at least 17 years of age at course commencement
✔ Entry is open with the requirement of applicants being interviewed to ensure course suitability and specific learner needs from a pastoral care perspective
✔ International Students: IELTS score of at least 5.5 with no band score lower than 5.0 or equivalent
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