CQUniversity Unit Profile
COIT12213 Applied Artificial Intelligence
Applied Artificial Intelligence
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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 1 - 2023

Brisbane
Melbourne
Online
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

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.

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

Additional Textbook Information

The prescribed textbook can be accessed online at the CQUniversity Library website. Access may be limited. If you would prefer your own copy, purchase either paper or eBook versions at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code)

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: 06 Mar 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: 13 Mar 2023

Module/Topic

· Machine Learning Pipelines

· Feature Selection and Feature Engineering

Chapter

Chapter 3 and 4

Events and Submissions/Topic

Week 3 Begin Date: 20 Mar 2023

Module/Topic

· Classification And Regression Using Supervised Learning

· Predictive Analytics with Ensemble Learning

Chapter

Chapter 5 and 6

Events and Submissions/Topic

Week 4 Begin Date: 27 Mar 2023

Module/Topic

· Detecting Patterns with Unsupervised Learning

· Building Recommender Systems

Chapter

Chapter 7 and 8

Events and Submissions/Topic

Week 5 Begin Date: 03 Apr 2023

Module/Topic

· Logic Programming

· Heuristic Search Techniques

Chapter

Chapter 9 and 10

Events and Submissions/Topic

Assignment 1 Due: Week 5 Friday (7 Apr 2023) 11:55 pm AEST
Vacation Week Begin Date: 10 Apr 2023

Module/Topic

Chapter

Events and Submissions/Topic

Week 6 Begin Date: 17 Apr 2023

Module/Topic

· Genetic Algorithms and Genetic Programming

· Artificial Intelligence on The Cloud

Chapter

Chapter 11 and 12

Events and Submissions/Topic

Week 7 Begin Date: 24 Apr 2023

Module/Topic

  • Building Games with Artificial Intelligence
  • Building A Speech Recognizer

Chapter

Chapter 13 and 14

Events and Submissions/Topic

Week 8 Begin Date: 01 May 2023

Module/Topic

  • Natural Language Processing
  • Chatbots

Chapter

Chapter 15 and 16

Events and Submissions/Topic

Week 9 Begin Date: 08 May 2023

Module/Topic

  • Sequential Data and Time Series Analysis
  • Image Recognition

Chapter

Chapter 17 and 18

Events and Submissions/Topic

Assignment 2 Due: Week 9 Friday (12 May 2023) 11:55 pm AEST
Week 10 Begin Date: 15 May 2023

Module/Topic

· Neural Networks

· Deep Learning with Convolutional Neural Networks

Chapter

Chapter 19 and 20

Events and Submissions/Topic

Week 11 Begin Date: 22 May 2023

Module/Topic

  • Recurrent Neural Networks and Other Deep Learning Model
  • Creating Intelligent Agents with Reinforcement learning

Chapter

Chapter 21 and 22

Events and Submissions/Topic

Week 12 Begin Date: 29 May 2023

Module/Topic

Artificial Intelligence with Big Data

Chapter

Chapter 23

Events and Submissions/Topic

Assignment 3 Due: Week 12 Friday (2 June 2023) 11:55 pm AEST
Review/Exam Week Begin Date: 05 Jun 2023

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 12 Jun 2023

Module/Topic

Chapter

Events and Submissions/Topic

Term Specific Information

Unit coordinator: Dr. Nahina Islam

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. You will get 3 attempts to try the online quiz before the due date. The highest score will be considered.


Number of Quizzes


Frequency of Quizzes


Assessment Due Date

Week 5 Friday (7 Apr 2023) 11:55 pm AEST

Online


Return Date to Students

Marks will be displayed immediately after due date


Weighting
35%

Assessment Criteria

The students will be marked based on their ability to specifically answer the questions in the online quiz.


Referencing Style

Submission
Online

Submission Instructions
Submit via Moodle link

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 9 Friday (12 May 2023) 11:55 pm AEST

Submit online via Moodle link


Return Date to Students

Week 11 Friday (26 May 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

Submission Instructions
Only one member from the group should submit

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 (2 June 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?