This course aims to provide you with a basic but comprehensive foundation of neural networks and deep learning, including underlying principles, architectures, and learning algorithms of various types of deep neural networks that are essential for future applications of artificial intelligence and data science.
| AUs | 3.0 AUs |
| Grade Type | |
| Prerequisite | SC1004, SC1007, MH2802, MH1201, MH1403, SC1123 |
| Exam | 28 November 2026, 1.00 pm - 3.00 pm |
The Exam information shown may be subject to changes. Students are to check the finalised exam timetable with exam seat information, which will be available at the 'Examination Seating Arrangement' webpage, 2 weeks before start of examination.
Prerequisite Graph
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1430 | COMMON LEC (SCL4) 1430-1620 Fri LT19 | ||||
| 1500 | |||||
| 1530 | |||||
| 1600 | |||||
| 1630 | |||||
| 1700 | |||||
| 1730 | 10520 TUT (SCEL) 1730-1820 Wed LT19 Wk2-13 | ||||
| 1800 |
Other offerings
Other Relevant Mods
SC1001
Introduction To Computational Thinking & Programming
SC1004
Linear Algebra For Computing
SC1005
Digital Logic
SC1006
Computer Organisation & Architecture
SC1007
Data Structures & Algorithms
SC1008
C & C++ Programming
SC1013
Physics For Computing
SC1123
Math 1: Linear Algebra & Calculus For Computing
SC1301
Language & Logic