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SIT787 - Mathematics for Artificial Intelligence

Year:

2021 unit information

Important Update:

Unit delivery will continue to be provided in line with the most current COVIDSafe health guidelines. This may include a mix of on-campus and online activities. To find out how you are impacted, please check your unit sites for announcements and updates. Unit sites open one week prior to the start of each Trimester/Semester.

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Last updated: 4 June 2021

Enrolment modes:Trimester 1: Waurn Ponds (Geelong), Online
Trimester 2: Waurn Ponds (Geelong), Online
Credit point(s):1
EFTSL value:0.125
Unit Chair:Trimester 1: Asef Nazari
Trimester 2: Asef Nazari
Prerequisite:

Nil

Corequisite:

Nil

Incompatible with:

Nil

Typical study commitment:

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

Scheduled learning activities - campus:

3 x 1 hour class per week, 1 x 1 hour workshop per week

Scheduled learning activities - cloud:

1 x 1 hour scheduled online workshop per week

Content

This unit provides the fundamental mathematical and statistical knowledge to understand important concepts in Artificial Intelligence (AI) and Data Science (DS). The contents of the unit are selected carefully to cover the most frequent mathematical and statistical tools and techniques to help students easily learn technical topics in AI and DS, enabling students to obtain enough experience to expand their knowledge into new directions if required. The unit builds a strong bridge between simple and core mathematical and statistical concepts and advanced techniques that are used in developing modern algorithms in AI and DS.

ULO These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: Deakin Graduate Learning Outcomes
ULO1

Explain the role and application of mathematical concepts associate with artificial intelligence.

GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking
GLO5: Problem solving

ULO2

Identify and summarise mathematical concepts and technique covered in the unit needed to solve mathematical problems from artificial intelligence applications.

GLO1: Discipline-specific knowledge and capabilities
GLO4: Critical thinking
GLO5: Problem solving

ULO3

Verify and critically evaluate results obtained and communicate results to a range of audiences

GLO2: Communication
GLO4: Critical thinking

ULO4

Read and interpret mathematical notation and communicate the problem-solving approach used

GLO1: Discipline-specific knowledge and capabilities
GLO2: Communication

These Unit Learning Outcomes are applicable for all teaching periods throughout the year

Assessment

Assessment Description Student output Grading and weighting
(% total mark for unit)		 Indicative due week
Problem Solving Task 1 Written responses to mathematical problems 10% Week 4
Problem Solving Task 2 Written responses to mathematical problems 15% Week 8
Problem Solving Task 3 Written responses to mathematical problems 15% Week 11
Examination 2-hour written examination 60% Examination period

The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.

Hurdle requirement

To be eligible to obtain a pass in this unit, students must achieve a mark of at least 50% in the examination.

Learning Resource

The texts and reading list for the unit can be found on the University Library via the link below: SIT787 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.

Unit Fee Information

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