This course introduces basic concepts and methodologies for machine learning as well as their applications. Clustering. Dimension Reduction. Classification. Decision Theory. Density Estimation. Classifier Evaluation.
| AUs | 3.0 AUs |
| Grade Type | |
| Prerequisite | Year 3 standing SC1004, SC1007, SC2000, MH2500 |
| Not Available To Programme | |
| Not Available To All Programme With | Yr1, Yr2, (Admyr 2011-2020) |
| Not Available As BDE/UE To Programme | MACS, MAEO(BA), MATH(BA) |
| Not Available As Core To Programme | |
| Not Available As PE To Programme | |
| Mutually Exclusive With | CE4041, CZ4041, MH4510, SC5002 |
| Not Offered As BDE | |
| Not Offered As Unrestricted Elective | Yes |
| Exam |
Total hours per week: 3 hrs
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1230 | 10508 TUT (SCEL) 1230-1320 Mon LT20 Wk2-13 | ||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | COMMON LEC (SCL4) 1430-1620 Wed LT19 | ||||
| 1500 | |||||
| 1530 | |||||
| 1600 |
Other offerings
Other Relevant Mods
SC1003
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
SC1104
Linear Algebra For Computing
SC1124
Math 2: Discrete Structures For Computing
SC1302
Ethics