CQUniversity Unit Profile
COIT12213 Applied Artificial Intelligence
Applied Artificial Intelligence
All details in this unit profile for COIT12213 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

Artificial Intelligence (AI) involves developing systems that are autonomous and intelligent. This unit introduces you to contemporary and emerging AI technologies to address problems such as medical diagnosis, manufacturing optimisation and transport scheduling. You will investigate the application of AI technologies in areas such as computer vision, machine learning and deep learning. Fundamental AI concepts will be considered, including artificial neural networks and model validation techniques. You will develop AI systems using industry tools and learn to develop a business case for an AI system.

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

Pre-requisite: COIT11222 Programming Fundamentals

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 2 - 2023

Online

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

Recommended Student Time Commitment

Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.

Class Timetable

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Online Quiz(zes)
Weighting: 35%
2. Group Work
Weighting: 30%
3. Written Assessment
Weighting: 35%

Assessment Grading

This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of ‘pass’ in order to pass the unit. If any ‘pass/fail’ tasks are shown in the table above they must also be completed successfully (‘pass’ grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the ‘assessment task’ section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University’s Grades and Results Policy for more details of interim results and final grades.

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 Teaching Team

Feedback

Students feel overloaded with many new theoretical and practical concepts each week, making it difficult for some students to grasp key AI concepts.

Recommendation

Increase practical materials on important AI topics, such as image analysis, face recognition and deep learning models, while reducing some of the theory on less important topics.

Feedback from Head of Postgraduate ICT courses

Feedback

The Moodle site can be streamlined to make it more user-friendly and consistent to adhere with CQURenew guidelines.

Recommendation

Streamline the Moodle site to make it more consistent to adhere with CQURenew guidelines.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Select Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges
  2. Apply industry tools to solve AI problems
  3. Critique business cases for AI systems against social and ethical frameworks.

The Australian Computer Society (ACS) recognises the Skills Framework for the Information Age (SFIA). SFIA provides a consistent definition of ICT skills. SFIA is adopted by organisations, governments, and individuals in many countries and is increasingly used when developing job descriptions and role profiles.

ACS members can use the tool MySFIA to build a skills profile at https://www.acs.org.au/professionalrecognition/mysfia-b2c.html.

The Australian Computer Society (ACS) recognises the Skills Framework for the Information Age (SFIA). SFIA is adopted by organisations, governments and individuals in many countries and provides a widely used and consistent definition of ICT skills. SFIA is increasingly being used when developing job descriptions and role profiles. ACS members can use the tool MySFIA to build a skills profile.

This unit contributes to the following workplace skills as defined by SFIA 7 (the SFIA code is included)

  • Analytics (INAN)
  • Systems design (DESN)
  • Data modelling and design (DTAN)
  • Programming/Software Development (PROG)

Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3
1 - Online Quiz(zes) - 35%
2 - Group Work - 30%
3 - Written Assessment - 35%

Alignment of Graduate Attributes to Learning Outcomes

Graduate Attributes Learning Outcomes
1 2 3
1 - Communication
2 - Problem Solving
3 - Critical Thinking
4 - Information Literacy
5 - Team Work
6 - Information Technology Competence
7 - Cross Cultural Competence
8 - Ethical practice
9 - Social Innovation
10 - Aboriginal and Torres Strait Islander Cultures

Alignment of Assessment Tasks to Graduate Attributes

Assessment Tasks Graduate Attributes
1 2 3 4 5 6 7 8 9 10
1 - Online Quiz(zes) - 35%
2 - Group Work - 30%
3 - Written Assessment - 35%
Textbooks and Resources

Textbooks

Prescribed

Artificial Intelligence with Python

second edition (2020)
Authors: Artificial Intelligence with Python
ISBN: 9781839219535
Binding: Website Link

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • Jupyter Notebook
Referencing Style

All submissions for this unit must use the referencing style: Harvard (author-date)

For further information, see the Assessment Tasks.

Teaching Contacts
Nahina Islam Unit Coordinator
n.islam@cqu.edu.au
Schedule
Week 1 Begin Date: 10 Jul 2023

Module/Topic

· Introduction To Artificial Intelligence

· Fundamental Use Cases for Artificial Intelligence

Chapter

Chapter 1 and 2

Events and Submissions/Topic

Week 2 Begin Date: 17 Jul 2023

Module/Topic

· Machine Learning Pipelines

· Feature Selection and Feature Engineering

Chapter

Chapter 3 and 4

Events and Submissions/Topic

Week 3 Begin Date: 24 Jul 2023

Module/Topic

 Classification And Regression Using Supervised Learning


Chapter

Chapter 5 

Events and Submissions/Topic

Week 4 Begin Date: 31 Jul 2023

Module/Topic

Predictive Analytics with Ensemble Learning


Chapter

Chapter 6


Events and Submissions/Topic

Week 5 Begin Date: 07 Aug 2023

Module/Topic

Detecting Patterns with Unsupervised Learning

Building Recommender Systems

Chapter

Chapter 7 & 8

Events and Submissions/Topic

Assignment 1 Due: Week 5 Friday (11 Aug 2023) 11:55 pm AEST
Vacation Week Begin Date: 14 Aug 2023

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 21 Aug 2023

Module/Topic

Image and video analysis

Chapter

Chapter 18

Events and Submissions/Topic

Week 7 Begin Date: 28 Aug 2023

Module/Topic

Heuristic Search Techniques

Chapter

Chapter 10

Events and Submissions/Topic

Week 8 Begin Date: 04 Sep 2023

Module/Topic

Building Games with Artificial Intelligence

Chapter

Chapter 13

Events and Submissions/Topic

Assignment 2 Due: Week 8 Friday (8 Sept 2023) 11:55 pm AEST
Week 9 Begin Date: 11 Sep 2023

Module/Topic

Chatbots


Chapter

Chapter 16


Events and Submissions/Topic

Week 10 Begin Date: 18 Sep 2023

Module/Topic

AI on the cloud 

AI and Ethics

Chapter

Chapter 12

Events and Submissions/Topic

Week 11 Begin Date: 25 Sep 2023

Module/Topic

Neural Networks

Chapter

Chapter 19

Events and Submissions/Topic

Week 12 Begin Date: 02 Oct 2023

Module/Topic

Deep Learning with Convolutional Neural Networks

Chapter

Chapter 20

Events and Submissions/Topic

Assignment 3 Due: Week 12 Friday (6 Oct 2023) 11:55 pm AEST
Review/Exam Week Begin Date: 09 Oct 2023

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 16 Oct 2023

Module/Topic

Chapter

Events and Submissions/Topic

Term Specific Information

Dear COIT12213 students,

Welcome to Term 2 2023!

I am Dr. Nahina Islam, the unit coordinator of COIT12213- Applied Artificial Intelligence. I hope you will enjoy the journey of learning applied Artificial Intelligence with me.

Warm wishes,

Dr. Nahina Islam

n.islam@cqu.edu.au


email: n.islam@cqu.edu.au

Assessment Tasks

1 Online Quiz(zes)

Assessment Title
Assignment 1

Task Description

Assessment 1 is an online quiz which is based on contents from Lecture 1-5. Through this assessment students will demonstrate their ability to select Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges. Students will get only one (1) attempt to take the online quiz before the due date.

Detailed information about this assignment can be accessed from the unit website in Moodle.


Number of Quizzes

1


Frequency of Quizzes

Other


Assessment Due Date

Week 5 Friday (11 Aug 2023) 11:55 pm AEST

Online


Return Date to Students

Score will be displayed immediately after completing the quiz


Weighting
35%

Assessment Criteria

Assessment 1 will cover the contents from Lecture 1-5. There will be 20 questions  which may be combination of Multiple choice, True/False and/or short answer questions. Students need to complete it within 1 hour. Students will get only one (1) attempt to take the online quiz before the due date.


Referencing Style

Submission
Online

Submission Instructions
The quiz link will be provided on Moodle

Learning Outcomes Assessed
  • Select Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges


Graduate Attributes
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Information Technology Competence

2 Group Work

Assessment Title
Assignment 2

Task Description

Assignment-2 is a group work where students have to write python code to solve the given problem(s). Students have to choose specific AI tool(s) to solve the problem(s) and have to justify the reason of choosing the specific AI tool(s). This assessment will address the following unit learning outcomes: Apply industry tools to solve AI problems and critique business cases for AI systems against social and ethical frameworks.



Assessment Due Date

Week 8 Friday (8 Sept 2023) 11:55 pm AEST

Submit online via Moodle link


Return Date to Students

Week 10 Friday (22 Sept 2023)

Online


Weighting
30%

Assessment Criteria

The students will be marked based on their ability to:

- Choose the correct AI tool and justifying the reason of this choice

- Writing the correct Python code

- Apply industry tools to solve AI problems

- Critique business cases for AI systems against social and ethical frameworks.


Referencing Style

Submission
Online Group

Learning Outcomes Assessed
  • Apply industry tools to solve AI problems
  • Critique business cases for AI systems against social and ethical frameworks.


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Team Work
  • Information Technology Competence
  • Cross Cultural Competence
  • Ethical practice
  • Social Innovation

3 Written Assessment

Assessment Title
Assignment 3

Task Description

Assignment 3 is an individual task where students have to develop python code to solve the given real-world problem(s). Students have to choose specific AI tool to solve the given problem and have to justify the reason of choosing the specific AI tool. This assessment will address the following unit learning outcomes: select Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges; apply industry tools to solve AI problems and critique business cases for AI systems against social and ethical frameworks.


Assessment Due Date

Week 12 Friday (6 Oct 2023) 11:55 pm AEST

Submit online via the Moodle link


Return Date to Students

On certification of grade


Weighting
35%

Assessment Criteria

The students will be marked based on their ability to:

- Ability to choose Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges

- Justifying the reason of this choice

- Develop the correct Python code

- Apply industry tools to solve AI problems

- Critique business cases for AI systems against social and ethical frameworks.


Referencing Style

Submission
Online

Submission Instructions
Submit online via Moodle link

Learning Outcomes Assessed
  • Select Artificial Intelligence (AI) techniques to solve authentic problems including social innovation challenges
  • Apply industry tools to solve AI problems
  • Critique business cases for AI systems against social and ethical frameworks.


Graduate Attributes
  • Communication
  • Problem Solving
  • Critical Thinking
  • Information Literacy
  • Information Technology Competence
  • Cross Cultural Competence
  • Ethical practice
  • Social Innovation

Academic Integrity Statement

As a CQUniversity student you are expected to act honestly in all aspects of your academic work.

Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.

When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.

Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.

As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.

What is a breach of academic integrity?

A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.

Why is academic integrity important?

A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.

Where can I get assistance?

For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.

What can you do to act with integrity?