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This course examines concepts, methods and tools to demonstrate the return on investment (ROI) of marketing activities and to leverage on data and marketing analytics to make better and more informed marketing decisions. Course topics covered include customer lifetime value, segmentation, targeting, positioning, forecasting, conjoint analysis etc. The course requires students to take prerequisites.
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This course focuses on implementing programs in the imperative paradigm using the C language under a UNIX operating system. It utilizes programming skills, compilation, and debugging aspects. Notions of name scope, lifespan and typing of variables, and recursion are also studied.
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COURSE DETAIL
COURSE DETAIL
This course examines algorithms, tools, practices, and applications of machine learning. Topics include core methods such as supervised learning (classification and regression), unsupervised learning (clustering, principal component analysis), Bayesian estimation, neural networks; common practices in data pre-processing, hyper-parameter tuning, and model evaluation; tools/libraries/APIs such as scikit-learn, Theano/Keras, and multi/many-core CPU/GPU programming.
COURSE DETAIL
COURSE DETAIL
This course covers basic knowledge of computers, including networks, office software, web basics, and Word, Excel, and PowerPoint in Microsoft Office 2016 packages.
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COURSE DETAIL
COURSE DETAIL
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