In this era of information, vast amounts of new data are produced every day from various fields including scientific research,healthcare, industry and service processes. Using data effectively and extracting meaningful insights from data can significantly improve efficiencies, cut costs and add more value to organizations. This course aims to provide you with an understanding of basic techniques for data analysis, machine learning and dimension reduction for big data, and expose you to hands-on computational tools that are fundamental for data science. Besides supervised and unsupervised learning,another fundamental technology of Artificial Intelligence - reinforcement learning will also be introduced,including Markov decision process and Q- learning. Suited for anyone from different backgrounds, this course will show you how you could apply various methods to data examples and case studies from both research and industrial sources in the Singapore context.
Academic Units | 3 |
Exam Schedule | Mon May 05 2025 00:00:00 GMT+0000 (Coordinated Universal Time) 13:00-15:00 |
Grade Type | Letter Graded |
Department Maintaining | SPS |
Prerequisites | PS0001 OR CZ1003 (Applicable to MACS) OR CZ1103 (Applicable to MACS) |
Mutually Exclusive | CE1015, CE1115, CE4073, CH0494, CZ1015, CZ1016, CZ1115, CZ4073, SC1015 |
Not Available to All Programme | (Admyr 2011-2017)-Non Direct Entry, (Admyr 2011-2018)-Direct Entry |
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1730
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