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.
| Academic Units | 3 |
| Exam Schedule | Not Applicable |
| Grade Type | Letter Graded |
| Department Maintaining | CE |
| Prerequisites | CE1007 & CE1011 & CE1012 OR CE1004 & CE1107 OR CE1004 & CE1007 OR CE1104 & CE1107 |
| Mutually Exclusive | |
| Not Available to Programme | ACBS, ACC, ADM, AERO, ARED, ASEC, BCG, BEEC, BIE, BMS, BS, BSB, BSPY, BUS, CBE, CBEC, CEE, CEE 1, CHEM, CHIN, CS, CSC, CSEC, CVEC, DSAI, ECMA, ECON, ECPP, ECPS, EEE, EEE 1, EEEC, EESS, ELAH, ELH, ENE, ENE 1, ENEC, ENG, ESPP, HIST, IEEC, IEM, LMS, MACS, MAEC, MAEO, MAT, MATH, ME 1, ME(DES), ME(IMS), ME(NULL), ME(RMS), MEEC(DES), MEEC(NULL), MEEC(RMS), MS, MS-2ndMaj/Spec(MSB), MTEC, PESC, PHIL, PHY, PPGA, PSLM, PSMA, PSY, REP(ASEN), REP(BIE), REP(CBE), REP(CSC), REP(CVEN), REP(EEE), REP(ENE), REP(MAT), REP(ME), ROBO, SCED, SOC, SSM |
| Not Available to All Programme | (Admyr 2021-onwards), |
| Index | Type | Group | Day | Time | Venue | Remark |
|---|
0930
1030
1130
1230
1330
1430
1530
1630
1730
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