Qualification

Micro-credential, NZQF Level 6

5 credits

Intake Dates
Course Fees
Domestic $1,199.00 NZD
International N/A
Admission Requirements

This micro-credential is open entry to New Zealand domestic students over the age of 18.

Portfolio Requirements

N/A

Overview

Course Overview

Building on the skills gained in Data Science Essentials 1, this flexible, online course examines the various processes used to identify patterns in collected data and how to construct data sets to solve distinct data science problems. 

In just six weeks, you’ll learn to develop data into different models, evaluate these models and use them to create stories. You’ll learn to apply this knowledge to different domains, deploy the models created and refine them based on feedback, as well as exploring and rationalising ethical and privacy issues related to data science.

 

What is a micro-credential?

A micro-credential is a self-directed online course of study, where you will work through the course material in a flexible manner (within a set overall duration, for example 6 weeks) and complete an assessment to gain a credential. There are no classes, but you will have access to an academic subject matter expert who will support you as you work on your assessment and grade your assessment at the end of the course. Micro-credentials, once successfully completed, can also count towards a full qualification if you wanted to continue your study in a particular field - check each micro-credential for details.

Course Outline

What you'll cover in this course

This course is designed to be undertaken online, in a self-directed fashion. It should take 51 hours to complete this micro-credential and it is recommended that you allocate about 17 hours of self-paced learning to each unit. The content is divided into three units, which each consist of three modules. Your facilitator will provide more instructions on how to split your time over the weeks available in this course. 

Additionally, these units aim to achieve a number of unit learning outcomes that will help shape your understanding of data science.