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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 | CZ1007, CZ1011, CZ1012, CZ1104, CZ1107, MH2802 |
| Not Available To Programme | ACBS, ACC, ADM, AERO, ARED, ASEC, BEEC, BIE, BMS, BS, BSB, BSPY, BUS, CBE, CBEC, CEE, CEE 1, CEEC, CHEM, CHIN, CS, CVEC, ECMA, ECON, ECPP, ECPS, EEE, EEE 1, EEEC, EESS, ELAH, ELH, ENE, ENE 1, ENEC, ENG, ESPP, HIST, IEEC, IEM, LMS, MAEC, MAEO(BA), MAEO(PMAS), MAEO(STAT), MAT, MATH(BA), MATH(PMAS), MATH(STAT), 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(CE), REP(CVEN), REP(EEE), REP(ENE), REP(MAT), REP(ME), ROBO, SCED, SOC, SSM |
| Not Available To All Programme With | (Admyr 2021-onwards), |
| Not Available As BDE/UE To Programme | |
| Not Available As Core To Programme | |
| Not Available As PE To Programme | |
| Mutually Exclusive With | CE4042, SC4001 |
| Not Offered As BDE | Yes |
| Not Offered As Unrestricted Elective | |
| Exam |
Required first
CZ1007Data StructuresCZ1011Engineering Mathematics ICZ1012Engineering Mathematics IiCZ1104Linear Algebra For ComputingCZ1107Data Structures & AlgorithmsMH2802Linear Algebra For ScientistsNeural Network & Deep Learning
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| 1630 | 10709 TUT (SCEL) 1630-1720 Wed LT3 Wk2-13 | ||||
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