SIT787 - Mathematics for Artificial Intelligence
| Year: | 2024 unit information |
|---|---|
| Enrolment modes: | Trimester 1: Waurn Ponds (Geelong), Online Trimester 2: Waurn Ponds (Geelong), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Prerequisite: | Nil |
| Corequisite: | Nil |
| Incompatible with: | Nil |
| Study commitment | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Scheduled learning activities - campus | 1 x 1 hour online lecture per week, 1 x 2 hour practical experience (workshop) per week. |
| Scheduled learning activities - online | Online independent and collaborative learning including 1 x 1 hour online lecture per week (recordings provided), 1 x 2 hour online practical experience (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.
Hurdle requirement
To be eligible to obtain a pass in this unit, students must achieve a mark of at least 40% in the End-of-Unit Assessment.
Unit Fee Information
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