This course is designed to equip you with the essential skills and practical knowledge to harness machine learning techniques for accelerating materials discovery and design. Specifically tailored for students interested in materials science, chemistry, physics, and engineering, it provides hands-on experience with core and advanced machine learning methods-including neural networks, optimization strategies, and generative modeling-to tackle real-world materials science problems. By mastering these data-driven approaches, you'll enhance your research capabilities, prepare for cutting-edge industry roles, and lay a strong foundation for future coursework or careers at the intersection of artificial intelligence and materials innovation.
Academic Units | 2 |
Exam Schedule | Not Applicable |
Grade Type | Letter Graded |
Department Maintaining | MAT |
Prerequisites | MS0003 & MS1008 OR BG2211 & CB0494 OR CB0494 & CH2107 OR CV0003 & CV1014 OR SC1003 & SC1015 OR EE0005 & EE1005 OR MA0218 & MA1008 OR IE0005 & IE1005 |
Index | Type | Group | Day | Time | Venue | Remark |
---|---|---|---|---|---|---|
15571 | LEC/STUDIO | LE | FRI | 0830-0920 | E-STUDIO | Teaching Wk1-8 |
15571 | TUT | T1 | FRI | 0830-1220 | E-STUDIO | Teaching Wk1-8 |
0930
1030
1130
1230
1330
1430
1530
1630
1730
MS4672
TUT | E-STUDIO
Teaching Wk1-8
MS4672
LEC/STUDIO | E-STUDIO
Teaching Wk1-8
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