This course provides an introductory but broad perspective of machine learning fundamental
algorithms, and is relevant for anyone pursuing a career in AI or Data Science. It aims to provide you with the essential concepts and principles of algorithms in machine learning so that you can use various machine learning techniques to solve real-world application problems.
| AUs | 3.0 AUs |
| Grade Type | |
| Prerequisite | SC1004, SC1007, SC2000, MH2500, AB1202, SC1123 |
| Exam | 25 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
Required first
AB1202Statistics & AnalysisMH2500ProbabilitySC1004Linear Algebra For ComputingSC1007Data Structures & AlgorithmsSC1123Math 1: Linear Algebra & Calculus For ComputingSC2000Probability & Statistics For ComputingMachine Learning
Unlocks
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1030 | COMMON LEC (SCL4) 1030-1220 Tue LT2A | ||||
| 1100 | |||||
| 1130 | |||||
| 1200 | |||||
| 1230 | 10519 TUT (SCEL) 1230-1320 Tue LT2A Wk2-13 | ||||
| 1300 |
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