The advent of the big data era has highlighted great new opportunities and challenges for statistical inference in manufacturing and daily life. To embrace big data (from an industrial manufacturing perspective), there is an urgent need to truly understand the core concepts and become capable of leveraging key algorithms/techniques/methodologies pertaining to data (big-data) statistics and computational inference, which is essential for extracting useful and valuable information for informed decision-making. This course will start with the core principles of data analytics and will equip you with the statistics and computational inference (including regression, dimensionality reduction, modeling) suitable for coping with big data case scenarios. This course is expected to help students develop interpretation of easy-to-use techniques/algorithms/methods and equip the students with essential skills in addressing big data inference problems in the chemical and biomedical industries.
| Academic Units | 3 |
| Exam Schedule | Mon May 05 2025 00:00:00 GMT+0000 (Coordinated Universal Time) 09:00-11:00 |
| Grade Type | Letter Graded |
| Department Maintaining | CBE |
| Prerequisites | |
| Not Available to Programme | ACBS, ACC, ADM, AERO, AISC, ARED, ASEC, BACF, BASA, BCE, BCG, BMS, BS, BSB, BUS, CE, CEE, CEEC, CHEM, CHIN, CMED, CNEL, CNLM, COMP, CS, CSC, CSEC, CVEC, ECON, EEE, EEEC, EESS, ELH, ELHS, ELPL, ENE, ENEC, ENG, HIST, HSCN, HSLM, IEEC, IEM, LMEL, LMPL, LMS, MACS, MAEC, MAT, MATH, ME(DES), ME(IMS), ME(NULL), ME(RMS), MEEC(DES), MEEC(NULL), MEEC(RMS), MS, MS-2ndMaj/Spec(MSB), MTEC, PHIL, PHY, PLCN, PLHS, PPGA, PSY, REP(ASEN), REP(BIE), REP(CBE), REP(CE), REP(CSC), REP(CVEN), REP(EEE), REP(ENE), REP(MAT), REP(ME), SCED, SOC, SPPE, SSM |
| Not Available to All Programme | Yr1, Yr2 |
| Index | Type | Group | Day | Time | Venue | Remark |
|---|
0930
1030
1130
1230
1330
1430
1530
1630
1730
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