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Artificial Intelligence
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ITECH2111 - Artificial Intelligence
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20250100
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Course
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Unit
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3.2
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2026-09-10
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2026-09-10
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Information Technology
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Institute of Innovation, Science & Sustainability
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Information Technology
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Undergraduate
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15
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.125
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020119
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Artificial Intelligence
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020119 - Artificial Intelligence
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<a href="http://www.federation.edu.au/locate/unit/itech2111">View unit fees</a>
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Graded (e.g. HD, D, C, etc)
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7
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Bachelor Degree
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Intermediate
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1
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<p>This unit provides you with an introduction to artificial intelligence and its relationship to other disciplines. You will be looking at the historical and contemporary contexts, and considering future trends. Whilst delving into the major fields of artificial intelligence solutions, there is an emphasis on knowledge representation, automated reasoning, predictive modelling, problem solving and in particular machine learning.</p>
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<p>Topics may include:<br>
1. History and philosophy behind artificial intelligence; current and future applications of artificial intelligence; social implications of AI<br>
2. Logic and search;<br>
3. Knowledge representation, and reasoning - including reasoning with uncertainty;<br>
4. Machine learning - overview, development processes and tools<br>
5. Supervised and semi-supervised learning<br>
6. Dimension reduction, clustering and unsupervised learning;<br>
7. Neural networks and deep learning; deep learning architectures<br>
8. Reinforcement learning</p>
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<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
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0200
Year
Year
2027
Current Year
2026
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ITECH2111 - Artificial Intelligence
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ITECH2111 - Artificial Intelligence
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Year
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2026
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Overview
Key information
Requisites
Learning outcomes
Assessment
FedTASK
Parent Region
Overview
Unit description
<p>This unit provides you with an introduction to artificial intelligence and its relationship to other disciplines. You will be looking at the historical and contemporary contexts, and considering future trends. Whilst delving into the major fields of artificial intelligence solutions, there is an emphasis on knowledge representation, automated reasoning, predictive modelling, problem solving and in particular machine learning.</p>
Unit content
<p>Topics may include:<br> 1. History and philosophy behind artificial intelligence; current and future applications of artificial intelligence; social implications of AI<br> 2. Logic and search;<br> 3. Knowledge representation, and reasoning - including reasoning with uncertainty;<br> 4. Machine learning - overview, development processes and tools<br> 5. Supervised and semi-supervised learning<br> 6. Dimension reduction, clustering and unsupervised learning;<br> 7. Neural networks and deep learning; deep learning architectures<br> 8. Reinforcement learning</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
020119 - Artificial Intelligence
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/itech2111">View unit fees</a>
Requisites
Prerequisite
<p>must have completed "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH1100" target="_blank">ITECH1100</a>" and must have completed 1 of "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH1400" target="_blank">ITECH1400</a>" / "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH2001" target="_blank">ITECH2001</a>"</p>
Corequisite
None
Exclusion
<p>must not have completed "<a href="/ords/r/curriculum/catalogue/course?p6_code=ITECH7001" target="_blank">ITECH7001</a>"</p>
Learning outcomes
Learning outcomes
<p>On successful completion of this unit, students are expected to gain the following [K]nowledge, [S]kills and [A]pplication of knowledge & skills</p>
Learning Outcomes
Ref
Outcome
K1
<p>Identify and explain a range of Artificial Intelligence algorithms and methodologies for solving complex problems;</p>
K2
<p>Recognize and outline historical and current progress across a range of Artificial Intelligence approaches.</p>
K3
<p>Explain how to design and deploy artificial intelligence so as to produce beneficial and equitable outcomes for society.</p>
S1
<p>Represent knowledge using different techniques to solve complex problems;</p>
S2
<p>Select, set up and apply appropriate algorithmic approaches for solving a variety of complex problems and real world situations;</p>
S3
<p>Apply abstract data models appropriate for a range of Artificial Intelligence solutions;</p>
S4
<p>Interpret, compare and report on algorithm performance in different contexts.</p>
A1
<p>Demonstrate initiative and judgement in adapting algorithms to unique and diverse contexts;</p>
A2
<p>Review and interpret appropriate developments in Artificial Intelligence.</p>
Assessment
Learning Tasks and Assessment
Supplementary assessment available:
Yes
Supplementary assessment information:
<p>Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment.</p>
FedTASK
FedTASK
Description of FedTASK outcome
Level
FedTASK 1: Interpersonal
The ability to effectively communicate, interact and work with others both individually and in groups.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 2: Leadership
The ability to apply professional skills and behaviours in leading others.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 3: Critical Thinking and Creativity
The ability to work in complexity and ambiguity using imagination to create new ideas.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK 4: Digital Literacy
The ability to work fluently across a range of tools and applications to achieve a range of skills.
<p>Level 3 - Student works independently with limited guidance or works within self-determined guidelines appropriate to context</p>
FedTASK 5: Sustainable and Ethical Mindset
The ability to consider and assess the consequences and impact of ideas and actions in enacting ethical and sustainable decisions.
<p>Level 2 - Student demonstrates some independence within provided guidelines</p>
FedTASK
<p>Federation University recognises that students require key transferable employability skills to prepare them for their future workplace and society. FedTASKs (<strong>T</strong>ransferable <strong>A</strong>ttributes <strong>S</strong>kills and <strong>K</strong>nowledge) provide a targeted focus on five key, transferable Attributes, Skills, and Knowledge that are embedded within curriculum, developed gradually towards successful measures and interlinked with cross-discipline and co-operative learning opportunities.</p>
Key information
Institute / school:
Institute of Innovation, Science & Sustainability
Discipline:
Information Technology
Study level:
Undergraduate
Credit points:
15
EFTSL:
0.125
Field of education:
020119 - Artificial Intelligence
Grade scheme:
Graded (e.g. HD, D, C, etc)
Placement component:
No
Fee information:
<a href="http://www.federation.edu.au/locate/unit/itech2111">View unit fees</a>
Additional information
Add Info Static Text
Internal reference: ITECH2111 - U3.2