fbpx
This error message is only visible to WordPress admins

No posts found.

Make sure this account has posts available on instagram.com.

Expanding Opportunity with Technology.

The aim of this micro credential is to provide learners with the knowledge and understanding in the fundamentals of cloud computing. Learners will use cloud computing components in business scenarios, describe and discuss the key concepts of modern cloud computing, understand the core services of the modern cloud, demonstrate operational knowledge for cloud security and compliance, and apply economic principles to cloud billing, accounts, and business proposals.

Upon completion of this micro-credential, learners/ākonga will be able to:

  • Discuss the main components of modern cloud systems
  • Identify and discuss the cloud models for different applications
  • Select and justify the core cloud services for business problems
  • Use the shared responsibility model to determine access management for cloud components
  • Identify and discuss the components of a total cost of ownership proposal

 

Contact Us

Qualification at a glance

Location & Duration

Cloud Fundamentals with QRC:

📍 Delivered from our Queenstown campus

📜 Certificate in Cloud Fundamentals (Level 5, 40 Credits)

📅 10 Weeks

Career Opportunities & Pathways

💻 Employment Pathway 

Graduates of the micro-credential will be able to apply the fundamentals of Cloud Computing to entry level roles in the New Zealand tech, corporate, Health and Education sectors as:

  • Entry-level Cloud Administrator
  • Entry-level IT support Specialist
  • Entry-level Cloud Security Analyst
  • Entry-level Cloud Sales Representative

👨🏼‍🎓 Study Pathway

Upon completion of this certificate learners will have gained the necessary skills and knowledge to proceed into further training in Cloud Computing and further study in data science, data engineering, and software development. 

Course Content
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.
Who is this course for?

✔ Suitable for school leavers, career changers, upskillers already in the business sector who want to expand their knowledge and skills in cloud computing 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

Find out more:

Cloud Computing in the News

Machine Learning with QRC

A Machine-Learning Algorithm Just Found 301 Additional Planets in Kepler Data

Machine Learning with QRC

Get used to hearing about machine Learning Start-Ups

This error message is only visible to WordPress admins

No posts found.

Make sure this account has posts available on instagram.com.