CQUniversity Unit Profile

In Progress

Please note that this Unit Profile is still in progress. The content below is subject to change.
COIT12209 Data Science
Data Science
All details in this unit profile for COIT12209 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

Overview

This unit focuses on the foundational concepts of data science. Digital data is growing at a very fast rate with data being the underlying driver of the knowledge economy. This unit will prepare you with foundational knowledge and practical skills about data collection, representation, storage, retrieval, management, analysis, and visualisation through the exploration of data-related challenges. You will also learn the impact of big data and business analytics on business performance to cater for the development of useful information and knowledge in an attempt to achieve data-driven decision making.  

Details

Career Level: Undergraduate
Unit Level: Level 2
Credit Points: 6
Student Contribution Band: 8
Fraction of Full-Time Student Load: 0.125

Pre-requisites or Co-requisites

Prerequisite: COIT11226 Systems Analysis Co-requisite: COIT11237 Database Design & Implementation

Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).

Offerings For Term 3 - 2025

Brisbane
Melbourne
Online
Rockhampton
Sydney

Attendance Requirements

All on-campus students are expected to attend scheduled classes – in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).

Class and Assessment Overview

Information for Class and Assessment Overview has not been released yet.

This information will be available on Monday 15 September 2025
Previous Student Feedback

Feedback, Recommendations and Responses

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Unit Evaluation

Feedback

Practice materials on the R language were insufficient.

Recommendation

Provide additional materials on R langauge.

Feedback from Unit Evaluation

Feedback

Big data lecture materials (i.e., Hadoop) were not updated.

Recommendation

Review the lecture slides on big data, and revamp the lecture materials.

Unit Learning Outcomes

Information for Unit Learning Outcomes has not been released yet.

This information will be available on Monday 15 September 2025
Alignment of Learning Outcomes, Assessment and Graduate Attributes

Information for Alignment of Learning Outcomes, Assessment and Graduate Attributes has not been released yet.

This information will be available on Monday 15 September 2025
Textbooks and Resources

Information for Textbooks and Resources has not been released yet.

This information will be available on Monday 20 October 2025
Academic Integrity Statement

Information for Academic Integrity Statement has not been released yet.

This unit profile has not yet been finalised.