COMP SCI 7318 - Deep Learning Fundamentals
Career: | Postgraduate Coursework |
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Units: | 3 |
Term: | 4339 |
Campus: | North Terrace |
Contact: | Up to 3 hours per week |
Available for Study Abroad and Exchange: | Yes |
Available for Non-Award Study: | No |
Pre-Requisite: | COMP SCI 7202 or (COMP SCI 7210 and COMP SCI 7211) |
Assessment: | Assignments and/or quizzes |
Syllabus: |
This course introduces key concepts underlying the development of deep learning techniques. These include: the place of deep learning in the context of statistics and machine learning; the definition, training and validation of deep models. A range of common models and their applications will be presented. The foundational ideas presented in this course will equip students to understand and interpret future developments in this fast moving field. |
Course Fees
Study Abroad student tuition fees are available here
Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information.
The fees displayed below for international students are for students commencing a program in 2024 only. International students who commenced a program in 2023 or prior can find their fee here.
EFTSL | |||
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0.125 |
Course Outline
A Course Outline which includes Learning Outcomes, Learning Resources, Learning & Teaching for this course may be accessed here
Critical Dates
Term | Last Day to Add Online | Census Date | Last Day to WNF | Last Day to WF |
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4339 | Mon 18/09/2023 | Wed 20/09/2023 | Fri 27/10/2023 | Wed 22/11/2023 |
Class Details
Enrolment Class: Workshop | |||||||
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Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
36006 | WR02 | 70 | 2 | 6 Sep - 22 Nov | Wednesday | 5pm - 6pm | Barr Smith South, 2032, Teaching Room | Note: This class will be delivered both online and face to face. Please refer to MyUni for details once enrolled. |
36064 | WR01 | 100 | 7 | 5 Sep - 21 Nov | Tuesday | 4pm - 5pm | Engineering & Mathematics, EM205, Teaching Room | Note: This class will be delivered both online and face to face. Please refer to MyUni for details once enrolled. |
Related Class: Lecture | |||||||
Class Nbr | Section | Size | Available | Dates | Days | Time | Location |
36065 | LE01 | 170 | 9 | 4 Sep - 20 Nov | Monday | 11am - 1pm | Mawson, G19, Mawson Lecture Theatre | Note: For an enriching and interactive learning experience, it is highly recommended to attend the lecture in person. While the lecture will be recorded, it is primarily intended for review purposes and for individuals who cannot attend due to special circumstances. Please check MyUni for details once enrolled. |