Statistics Computational Inference To Big Data
AY2022/2023 Semester 2
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.
| AUs | 3.0 AUs |
| Categories | CoreBDE |
| Not Available To Programme | ACBS, ACC, ADM, AERO, ARED, ASEC, BCE, BCG, BMS, BS, BSB, BUS, CE, CEE, CEEC, CHEM, CHIN, CNEL, CNLM, 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(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, SSM |
| Exam |
Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 930 | |||||
| 1000 | |||||
| 1030 | |||||
| 1100 | |||||
| 1130 | |||||
| 1200 | |||||
| 1230 | |||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | |||||
| 1500 | |||||
| 1530 | |||||
| 1600 | |||||
| 1630 | |||||
| 1700 | |||||
| 1730 | |||||
| 1800 |