Overview

This unit aims to introduce students to the key concepts and techniques in data science and Big Data analytics. Students will be introduced to different stages in data analytics and given the opportunity to plan and design data science projects that address business and organisational needs.

Requisites

Prerequisites
COS10022 Data Science Principles

Assumed Knowledge
Students are expected to have basic programming skills

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
03-March-2025
01-June-2025
Last self-enrolment date
16-March-2025
Census date
31-March-2025
Last withdraw without fail date
24-April-2025
Results released date
08-July-2025
Teaching Period 1
Location
Online
Start and end dates
10-March-2025
08-June-2025
Last self-enrolment date
23-March-2025
Census date
04-April-2025
Last withdraw without fail date
02-May-2025
Results released date
Teaching Period 3
Location
Online
Start and end dates
03-November-2025
08-February-2026
Last self-enrolment date
16-November-2025
Census date
28-November-2025
Last withdraw without fail date
02-January-2026
Results released date

Learning outcomes

Students who successfully complete this unit will be able to:

  • Appreciate the roles of data science and Big Data analytics in organisational contexts
  • Compare and analyse the key concepts, techniques and tools for discovering, analysing, visualising and presenting data
  • Describe the processes within the Data Analytics Lifecycle
  • Analyse organisational problems and formulate them into data science tasks
  • Evaluate suitable techniques and tools for specific data science tasks
  • Develop and execute an analytics plan for a given case study

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Live Online
Lecture
2.00 12 weeks 24
On-campus
Class
2.00 12 weeks 24
Online
Directed Online Learning and Independent Learning
1.00 12 weeks 12
Unspecified Activities
Independent Learning
7.50 12 weeks 90
TOTAL150

Sarawak

Type Hours per week Number of weeks Total (number of hours)
Online
Directed Online Learning and Independent Learning
12.50 12 weeks 150
On-campus
Lecture
2.00 12 weeks 24
On-campus
Class
2.00 12 weeks 24
Online
Directed Online Learning and Independent Learning
1.00 12 weeks 12
Unspecified Activities
Independent Learning
7.50 12 weeks 90
TOTAL300

Assessment

Type Task Weighting ULO's
Assignment 1Individual/Group 10 - 30% 4,5,6 
Assignment 2Individual/Group 10 - 30% 1,2,3 
Online TestsIndividual 5 - 15% 4,5,6 
Online TestsIndividual 5 - 15% 2,3,4,5,6 
Online TestsIndividual 30 - 50% 1,2,3,4,5,6 

Content

  • Introduction to Data Science and Big Data Analytics
  • Roles of Data Science for business
  • Contemporary data structures and management
  • Data Science tools, techniques and technologies
  • The Data Analytics Lifecycle
  • Analytical techniques and methods
  • Analytics plan development

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.