IFB220 Introduction to AI for IT Professionals
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | IFB220 |
|---|---|
| Prerequisite(s): | IFB104 or EGB103 |
| Equivalent(s): | IFZ220 |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
Unit Outline: Semester 1 2026, Gardens Point, Internal
| Unit code: | IFB220 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 or EGB103 |
| Equivalent: | IFZ220 |
Overview
In this unit, you'll discover how Artificial Intelligence (AI) is reshaping our world and driving unprecedented innovation, poised to revolutionize how we live and work. We'll cover the fundamental concepts and applications of AI, with a special focus on Generative AI. You'll learn how AI systems function, how they differ from human intelligence, and how to critically evaluate AI-generated information. We'll explore practical methods for integrating AI into IT systems, examine AI's impact on various industries, and discuss ethical, social, and legal concerns. You'll investigate how businesses plan to use AI to add value and enhance productivity, and assess the impact on jobs and skills. Through a mix of theoretical knowledge and practical exercises, you'll learn to effectively apply AI for ongoing learning, writing, and professional tasks. By the end of this unit, you'll be equipped with the foundational skills necessary to leverage AI in your future IT career.
Learning Outcomes
On successful completion of this unit you will be able to:
- Explain how current AI systems/models work and contrast AI with human intelligence.
- Use information generated by AI with confidence by critically analysing its reliability and validity.
- Explain the range of ways that companies can integrate AI into their IT systems, and demonstrate practical skills to implement simple systems integrations.
- Describe how businesses are planning to use AI to increase value and productivity in a variety of industries and evaluate the possible impact on jobs and skills in those areas.
- Effectively apply AI for your own ongoing learning, writing, and to conduct professional tasks more productively.
- Critically assess the ethical, social, legal and governance concerns related to AI, including in the context of academic and professional integrity and plagiarism.
Content
In this unit you will learn about:
- What is AI and how it has been understood over the years.
- What are General AI (GAI), Generative AI (GenAI), and Large Language Models (LLMs). What are their transformative potential and issues.
- How GenAI and LLMs are used in real-world applications.
- What are the most popular AI systems and how to use them in applications through available APIs.
- How to design a simple AI-infused software application and confidently use prompt engineering techniques.
- How to analyse the functioning of common AI models, including various types of neural networks, and critically evaluate the challenges related to training and fine-tuning large AI models.
- How to critically assess ethical, legal, and governance concerns related to AI systems, and demonstrate an understanding of the importance of responsible AI practices.
Learning Approaches
This unit is available for study in both on-campus and online modes. The unit consists weekly of lectures and tutorials.
Each week, you will have access to pre-recorded materials and readings, and you are expected to review this content before the weekly lecture. These resources will provide a basic framework to build your knowledge and understanding of covered topics. The lecture will be an opportunity for you to ask questions and will feature a mix of discussions, demonstrations, and in-depth analysis of the material.
Throughout the semester you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process, you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
You should expect to spend an average of 10 - 15 hours per week preparing for and attending scheduled classes, completing assessment tasks, and engaging in independent study to reinforce your learning.
Real World Learning
As a first year unit, you will be introduce to threshold concepts and key academic skills related to academic integrity and plagiarism in a post-AI world. The Student Success Group will also offer complementary support for learning, including drop-in peer support sessions each week. You will explore how Generative AI is impacting jobs and skills within the IT industry and how it can assist you in effectively exploring and managing your career. You will learn about industry-relevant digital practices and technologies, including GenAI-related tools and systems like ChatGPT, which are currently the most in-demand digital literacy skills. You will also learn about the significant electricity consumption of AI, which is comparable to that of a small country and is doubling roughly every 100 days. This knowledge aligns with SDG 7: Affordable and Clean Energy and SDG 13: Climate Action, as it highlights the need for sustainable energy practices and reducing carbon emissions.
Feedback on Learning and Assessment
You will receive feedback on portfolio of AI assisted learning and tasks from your peers and tutor at the weekly tutorial classes. You will also receive individual comments on the final version of your assignments when you submit them at the end of the semester. There will be a MS Teams channel used for addressing frequently asked questions in relation to the assessment items as well as a class email address ifb220@qut.edu.au for contacting the teaching team.
Assessment
Overview
Throughout the semester your will work on developing a portfolio of AI assisted learning and tasks. These will be presented and discussed in the weekly tutorial sessions with interim feedback and marks awarded every couple of weeks. The final portfolio is due at the end of the semester, but you will need to add to it progressively throughout the semester.
The other major assessment item will involve you implementing a simple software application that uses an API interface to talk to an AI service, so as to integrate AI into a custom software application to address a given challenge.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio of AI Assisted Learning and Tasks
In this assessment, you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
Milestones throughout the semester will be assessed in practical class.
The final end of semester submission is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Integrate AI into a simple software application by using programming and APIs
In this assessment, you will embark on a hands-on journey to incorporate artificial intelligence into a basic software application that uses programming and APIs to integrate AI functionalities. The application will provide a chat interface to the user and its goal will be to advise the user on a specific topic. As a part of the task, you will have to ensure that the application is secure (it only allows discussing the topic specified in the assignment). You will also have to critically reflect on its capabilities and limitations, including the ethical, social, and governance aspects.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
All learning materials for this unit will be provided in your Canvas site.
Resource Materials
Recommended text(s)
We will add a recommend a text book if we can find a good one that covers most of the relevant material.
Software
Copilot AI-powered assistant
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Portfolio of AI Assisted Learning and Tasks - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, Portfolio of AI Assisted Learning and Tasks - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: ULO3, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Demonstrate an understanding of the role of IT in enabling business outcomes and how business realities shape IT decisions.
Relates to: ULO4, Portfolio of AI Assisted Learning and Tasks - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: ULO5, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Assess the risks and potential of artificial intelligence (and other disruptive emerging technologies) within an organisation and leverage AI knowledge and skills to solve IT challenges, improve productivity and add value.
Relates to: ULO1, ULO2, ULO3, ULO4, ULO5, ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs
Unit Outline: Semester 1 2026, Online
| Unit code: | IFB220 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 or EGB103 |
| Equivalent: | IFZ220 |
Overview
In this unit, you'll discover how Artificial Intelligence (AI) is reshaping our world and driving unprecedented innovation, poised to revolutionize how we live and work. We'll cover the fundamental concepts and applications of AI, with a special focus on Generative AI. You'll learn how AI systems function, how they differ from human intelligence, and how to critically evaluate AI-generated information. We'll explore practical methods for integrating AI into IT systems, examine AI's impact on various industries, and discuss ethical, social, and legal concerns. You'll investigate how businesses plan to use AI to add value and enhance productivity, and assess the impact on jobs and skills. Through a mix of theoretical knowledge and practical exercises, you'll learn to effectively apply AI for ongoing learning, writing, and professional tasks. By the end of this unit, you'll be equipped with the foundational skills necessary to leverage AI in your future IT career.
Learning Outcomes
On successful completion of this unit you will be able to:
- Explain how current AI systems/models work and contrast AI with human intelligence.
- Use information generated by AI with confidence by critically analysing its reliability and validity.
- Explain the range of ways that companies can integrate AI into their IT systems, and demonstrate practical skills to implement simple systems integrations.
- Describe how businesses are planning to use AI to increase value and productivity in a variety of industries and evaluate the possible impact on jobs and skills in those areas.
- Effectively apply AI for your own ongoing learning, writing, and to conduct professional tasks more productively.
- Critically assess the ethical, social, legal and governance concerns related to AI, including in the context of academic and professional integrity and plagiarism.
Content
In this unit you will learn about:
- What is AI and how it has been understood over the years.
- What are General AI (GAI), Generative AI (GenAI), and Large Language Models (LLMs). What are their transformative potential and issues.
- How GenAI and LLMs are used in real-world applications.
- What are the most popular AI systems and how to use them in applications through available APIs.
- How to design a simple AI-infused software application and confidently use prompt engineering techniques.
- How to analyse the functioning of common AI models, including various types of neural networks, and critically evaluate the challenges related to training and fine-tuning large AI models.
- How to critically assess ethical, legal, and governance concerns related to AI systems, and demonstrate an understanding of the importance of responsible AI practices.
Learning Approaches
This unit is available for study in both on-campus and online modes. The unit consists weekly of lectures and tutorials.
Each week, you will have access to pre-recorded materials and readings, and you are expected to review this content before the weekly lecture. These resources will provide a basic framework to build your knowledge and understanding of covered topics. The lecture will be an opportunity for you to ask questions and will feature a mix of discussions, demonstrations, and in-depth analysis of the material.
Throughout the semester you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process, you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
You should expect to spend an average of 10 - 15 hours per week preparing for and attending scheduled classes, completing assessment tasks, and engaging in independent study to reinforce your learning.
Real World Learning
As a first year unit, you will be introduce to threshold concepts and key academic skills related to academic integrity and plagiarism in a post-AI world. The Student Success Group will also offer complementary support for learning, including drop-in peer support sessions each week. You will explore how Generative AI is impacting jobs and skills within the IT industry and how it can assist you in effectively exploring and managing your career. You will learn about industry-relevant digital practices and technologies, including GenAI-related tools and systems like ChatGPT, which are currently the most in-demand digital literacy skills. You will also learn about the significant electricity consumption of AI, which is comparable to that of a small country and is doubling roughly every 100 days. This knowledge aligns with SDG 7: Affordable and Clean Energy and SDG 13: Climate Action, as it highlights the need for sustainable energy practices and reducing carbon emissions.
Feedback on Learning and Assessment
You will receive feedback on portfolio of AI assisted learning and tasks from your peers and tutor at the weekly tutorial classes. You will also receive individual comments on the final version of your assignments when you submit them at the end of the semester. There will be a MS Teams channel used for addressing frequently asked questions in relation to the assessment items as well as a class email address ifb220@qut.edu.au for contacting the teaching team.
Assessment
Overview
Throughout the semester your will work on developing a portfolio of AI assisted learning and tasks. These will be presented and discussed in the weekly tutorial sessions with interim feedback and marks awarded every couple of weeks. The final portfolio is due at the end of the semester, but you will need to add to it progressively throughout the semester.
The other major assessment item will involve you implementing a simple software application that uses an API interface to talk to an AI service, so as to integrate AI into a custom software application to address a given challenge.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio of AI Assisted Learning and Tasks
In this assessment, you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
Milestones throughout the semester will be assessed in practical class.
The final end of semester submission is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Integrate AI into a simple software application by using programming and APIs
In this assessment, you will embark on a hands-on journey to incorporate artificial intelligence into a basic software application that uses programming and APIs to integrate AI functionalities. The application will provide a chat interface to the user and its goal will be to advise the user on a specific topic. As a part of the task, you will have to ensure that the application is secure (it only allows discussing the topic specified in the assignment). You will also have to critically reflect on its capabilities and limitations, including the ethical, social, and governance aspects.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
All learning materials for this unit will be provided in your Canvas site.
Resource Materials
Recommended text(s)
We will add a recommend a text book if we can find a good one that covers most of the relevant material.
Software
Copilot AI-powered assistant
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Portfolio of AI Assisted Learning and Tasks - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, Portfolio of AI Assisted Learning and Tasks - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: ULO3, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Demonstrate an understanding of the role of IT in enabling business outcomes and how business realities shape IT decisions.
Relates to: ULO4, Portfolio of AI Assisted Learning and Tasks - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: ULO5, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Assess the risks and potential of artificial intelligence (and other disruptive emerging technologies) within an organisation and leverage AI knowledge and skills to solve IT challenges, improve productivity and add value.
Relates to: ULO1, ULO2, ULO3, ULO4, ULO5, ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs
Unit Outline: Semester 2 2026, Gardens Point, Internal
| Unit code: | IFB220 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 or EGB103 |
| Equivalent: | IFZ220 |
Overview
In this unit, you'll discover how Artificial Intelligence (AI) is reshaping our world and driving unprecedented innovation, poised to revolutionize how we live and work. We'll cover the fundamental concepts and applications of AI, with a special focus on Generative AI. You'll learn how AI systems function, how they differ from human intelligence, and how to critically evaluate AI-generated information. We'll explore practical methods for integrating AI into IT systems, examine AI's impact on various industries, and discuss ethical, social, and legal concerns. You'll investigate how businesses plan to use AI to add value and enhance productivity, and assess the impact on jobs and skills. Through a mix of theoretical knowledge and practical exercises, you'll learn to effectively apply AI for ongoing learning, writing, and professional tasks. By the end of this unit, you'll be equipped with the foundational skills necessary to leverage AI in your future IT career.
Learning Outcomes
On successful completion of this unit you will be able to:
- Explain how current AI systems/models work and contrast AI with human intelligence.
- Use information generated by AI with confidence by critically analysing its reliability and validity.
- Explain the range of ways that companies can integrate AI into their IT systems, and demonstrate practical skills to implement simple systems integrations.
- Describe how businesses are planning to use AI to increase value and productivity in a variety of industries and evaluate the possible impact on jobs and skills in those areas.
- Effectively apply AI for your own ongoing learning, writing, and to conduct professional tasks more productively.
- Critically assess the ethical, social, legal and governance concerns related to AI, including in the context of academic and professional integrity and plagiarism.
Content
In this unit you will learn about:
- What is AI and how it has been understood over the years.
- What are General AI (GAI), Generative AI (GenAI), and Large Language Models (LLMs). What are their transformative potential and issues.
- How GenAI and LLMs are used in real-world applications.
- What are the most popular AI systems and how to use them in applications through available APIs.
- How to design a simple AI-infused software application and confidently use prompt engineering techniques.
- How to analyse the functioning of common AI models, including various types of neural networks, and critically evaluate the challenges related to training and fine-tuning large AI models.
- How to critically assess ethical, legal, and governance concerns related to AI systems, and demonstrate an understanding of the importance of responsible AI practices.
Learning Approaches
This unit is available for study in both on-campus and online modes. The unit consists weekly of lectures and tutorials.
Each week, you will have access to pre-recorded materials and readings, and you are expected to review this content before the weekly lecture. These resources will provide a basic framework to build your knowledge and understanding of covered topics. The lecture will be an opportunity for you to ask questions and will feature a mix of discussions, demonstrations, and in-depth analysis of the material.
Throughout the semester you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process, you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
You should expect to spend an average of 10 - 15 hours per week preparing for and attending scheduled classes, completing assessment tasks, and engaging in independent study to reinforce your learning.
Real World Learning
As a first year unit, you will be introduce to threshold concepts and key academic skills related to academic integrity and plagiarism in a post-AI world. The Student Success Group will also offer complementary support for learning, including drop-in peer support sessions each week. You will explore how Generative AI is impacting jobs and skills within the IT industry and how it can assist you in effectively exploring and managing your career. You will learn about industry-relevant digital practices and technologies, including GenAI-related tools and systems like ChatGPT, which are currently the most in-demand digital literacy skills. You will also learn about the significant electricity consumption of AI, which is comparable to that of a small country and is doubling roughly every 100 days. This knowledge aligns with SDG 7: Affordable and Clean Energy and SDG 13: Climate Action, as it highlights the need for sustainable energy practices and reducing carbon emissions.
Feedback on Learning and Assessment
You will receive feedback on portfolio of AI assisted learning and tasks from your peers and tutor at the weekly tutorial classes. You will also receive individual comments on the final version of your assignments when you submit them at the end of the semester. There will be a MS Teams channel used for addressing frequently asked questions in relation to the assessment items as well as a class email address ifb220@qut.edu.au for contacting the teaching team.
Assessment
Overview
Throughout the semester your will work on developing a portfolio of AI assisted learning and tasks. These will be presented and discussed in the weekly tutorial sessions with interim feedback and marks awarded every couple of weeks. The final portfolio is due at the end of the semester, but you will need to add to it progressively throughout the semester.
The other major assessment item will involve you implementing a simple software application that uses an API interface to talk to an AI service, so as to integrate AI into a custom software application to address a given challenge.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio of AI Assisted Learning and Tasks
In this assessment, you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
Milestones throughout the semester will be assessed in practical class.
The final end of semester submission is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Integrate AI into a simple software application by using programming and APIs
In this assessment, you will embark on a hands-on journey to incorporate artificial intelligence into a basic software application that uses programming and APIs to integrate AI functionalities. The application will provide a chat interface to the user and its goal will be to advise the user on a specific topic. As a part of the task, you will have to ensure that the application is secure (it only allows discussing the topic specified in the assignment). You will also have to critically reflect on its capabilities and limitations, including the ethical, social, and governance aspects.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
All learning materials for this unit will be provided in your Canvas site.
Resource Materials
Recommended text(s)
We will add a recommend a text book if we can find a good one that covers most of the relevant material.
Software
Copilot AI-powered assistant
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Portfolio of AI Assisted Learning and Tasks - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, Portfolio of AI Assisted Learning and Tasks - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: ULO3, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Demonstrate an understanding of the role of IT in enabling business outcomes and how business realities shape IT decisions.
Relates to: ULO4, Portfolio of AI Assisted Learning and Tasks - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: ULO5, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Assess the risks and potential of artificial intelligence (and other disruptive emerging technologies) within an organisation and leverage AI knowledge and skills to solve IT challenges, improve productivity and add value.
Relates to: ULO1, ULO2, ULO3, ULO4, ULO5, ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs
Unit Outline: Semester 2 2026, Online
| Unit code: | IFB220 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 or EGB103 |
| Equivalent: | IFZ220 |
Overview
In this unit, you'll discover how Artificial Intelligence (AI) is reshaping our world and driving unprecedented innovation, poised to revolutionize how we live and work. We'll cover the fundamental concepts and applications of AI, with a special focus on Generative AI. You'll learn how AI systems function, how they differ from human intelligence, and how to critically evaluate AI-generated information. We'll explore practical methods for integrating AI into IT systems, examine AI's impact on various industries, and discuss ethical, social, and legal concerns. You'll investigate how businesses plan to use AI to add value and enhance productivity, and assess the impact on jobs and skills. Through a mix of theoretical knowledge and practical exercises, you'll learn to effectively apply AI for ongoing learning, writing, and professional tasks. By the end of this unit, you'll be equipped with the foundational skills necessary to leverage AI in your future IT career.
Learning Outcomes
On successful completion of this unit you will be able to:
- Explain how current AI systems/models work and contrast AI with human intelligence.
- Use information generated by AI with confidence by critically analysing its reliability and validity.
- Explain the range of ways that companies can integrate AI into their IT systems, and demonstrate practical skills to implement simple systems integrations.
- Describe how businesses are planning to use AI to increase value and productivity in a variety of industries and evaluate the possible impact on jobs and skills in those areas.
- Effectively apply AI for your own ongoing learning, writing, and to conduct professional tasks more productively.
- Critically assess the ethical, social, legal and governance concerns related to AI, including in the context of academic and professional integrity and plagiarism.
Content
In this unit you will learn about:
- What is AI and how it has been understood over the years.
- What are General AI (GAI), Generative AI (GenAI), and Large Language Models (LLMs). What are their transformative potential and issues.
- How GenAI and LLMs are used in real-world applications.
- What are the most popular AI systems and how to use them in applications through available APIs.
- How to design a simple AI-infused software application and confidently use prompt engineering techniques.
- How to analyse the functioning of common AI models, including various types of neural networks, and critically evaluate the challenges related to training and fine-tuning large AI models.
- How to critically assess ethical, legal, and governance concerns related to AI systems, and demonstrate an understanding of the importance of responsible AI practices.
Learning Approaches
This unit is available for study in both on-campus and online modes. The unit consists weekly of lectures and tutorials.
Each week, you will have access to pre-recorded materials and readings, and you are expected to review this content before the weekly lecture. These resources will provide a basic framework to build your knowledge and understanding of covered topics. The lecture will be an opportunity for you to ask questions and will feature a mix of discussions, demonstrations, and in-depth analysis of the material.
Throughout the semester you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process, you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
You should expect to spend an average of 10 - 15 hours per week preparing for and attending scheduled classes, completing assessment tasks, and engaging in independent study to reinforce your learning.
Real World Learning
As a first year unit, you will be introduce to threshold concepts and key academic skills related to academic integrity and plagiarism in a post-AI world. The Student Success Group will also offer complementary support for learning, including drop-in peer support sessions each week. You will explore how Generative AI is impacting jobs and skills within the IT industry and how it can assist you in effectively exploring and managing your career. You will learn about industry-relevant digital practices and technologies, including GenAI-related tools and systems like ChatGPT, which are currently the most in-demand digital literacy skills. You will also learn about the significant electricity consumption of AI, which is comparable to that of a small country and is doubling roughly every 100 days. This knowledge aligns with SDG 7: Affordable and Clean Energy and SDG 13: Climate Action, as it highlights the need for sustainable energy practices and reducing carbon emissions.
Feedback on Learning and Assessment
You will receive feedback on portfolio of AI assisted learning and tasks from your peers and tutor at the weekly tutorial classes. You will also receive individual comments on the final version of your assignments when you submit them at the end of the semester. There will be a MS Teams channel used for addressing frequently asked questions in relation to the assessment items as well as a class email address ifb220@qut.edu.au for contacting the teaching team.
Assessment
Overview
Throughout the semester your will work on developing a portfolio of AI assisted learning and tasks. These will be presented and discussed in the weekly tutorial sessions with interim feedback and marks awarded every couple of weeks. The final portfolio is due at the end of the semester, but you will need to add to it progressively throughout the semester.
The other major assessment item will involve you implementing a simple software application that uses an API interface to talk to an AI service, so as to integrate AI into a custom software application to address a given challenge.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio of AI Assisted Learning and Tasks
In this assessment, you will be given a series of tasks to complete, corresponding to each of the unit learning outcomes. For each task you will use prompt engineering to use AI to thoroughly investigate and learn about that topic. Your learnings will be presented and discussed in small groups at the weekly tutorials, with feedback and interim assessment provided by your peers and your tutor. Through this process you will progressively improve your skills in using AI as a learning aid, develop your skills in critically analysing the information provided by AI and verifying its validity. The process will also aid your ability to reflect on your own understanding of topics and how to formulate questions to get to the bottom of what you don't currently understand. Along the way you will regularly add to your portfolio, not just your finished findings, but more important the journey of enquiry that took you there.
Milestones throughout the semester will be assessed in practical class.
The final end of semester submission is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Integrate AI into a simple software application by using programming and APIs
In this assessment, you will embark on a hands-on journey to incorporate artificial intelligence into a basic software application that uses programming and APIs to integrate AI functionalities. The application will provide a chat interface to the user and its goal will be to advise the user on a specific topic. As a part of the task, you will have to ensure that the application is secure (it only allows discussing the topic specified in the assignment). You will also have to critically reflect on its capabilities and limitations, including the ethical, social, and governance aspects.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
All learning materials for this unit will be provided in your Canvas site.
Resource Materials
Recommended text(s)
We will add a recommend a text book if we can find a good one that covers most of the relevant material.
Software
Copilot AI-powered assistant
Risk Assessment Statement
There are no out-of-the-ordinary risks associated with this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Portfolio of AI Assisted Learning and Tasks - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, Portfolio of AI Assisted Learning and Tasks - Integrate and apply technical knowledge and skills to analyse, design, build, operate and maintain sustainable, secure IT systems using industry-standard tools, technologies, platforms, and processes.
Relates to: ULO3, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Demonstrate an understanding of the role of IT in enabling business outcomes and how business realities shape IT decisions.
Relates to: ULO4, Portfolio of AI Assisted Learning and Tasks - Demonstrate initiative, autonomy and personal responsibility for continuous learning, working both independently and collaboratively within multi-disciplinary teams, employing state-of-the-art IT project management methodologies to plan and manage time, resources, and risk.
Relates to: ULO5, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Assess the risks and potential of artificial intelligence (and other disruptive emerging technologies) within an organisation and leverage AI knowledge and skills to solve IT challenges, improve productivity and add value.
Relates to: ULO1, ULO2, ULO3, ULO4, ULO5, ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO6, Portfolio of AI Assisted Learning and Tasks, Integrate AI into a simple software application by using programming and APIs