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Module Detailed Information for [DSC3216]
Academic Year : 2017/2018 Semester : 2
Correct as at 20 Oct 2018 05:00

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Module Information
Module Code :
Module Title : Predictive Analytics in Business
Module Description : Managerial success rests strategically on the ability to forecast the demand for the goods and services that a firm provides. Demand forecasting drives the effective planning of the supply chain: personnel requirements, capital investment, production schedules, logistics etc.This module surveys forecasting techniques and their applications. These encompass traditional qualitative (e.g. front line intelligence, Delphi method) and quantitative techniques (e.g. regression, time series) as well as emerging techniques based on neural networks. Concepts such as trends, seasonality and business cycles will be discussed. Their value in improving forecasts will be illustrated. The module makes extensive use of software including MS Excel and dedicated forecasting packages.
Module Examinable : -
Exam Date : No Exam Date.
Modular Credits : 4
Pre-requisite : Nil
Preclusion : Nil
Module Workload (A-B-C-D-E)* : 0-3-0-3-4
Remarks : Nil
* A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of laboratory hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week

Lecture Time Table
Class TypeWeek TypeWeek DayStartEndRoom

Tutorial Time Table
Attention: The tutorial timetables could be updated from time to time. Students are advised to check regularly for the latest update on the change of tutorial timing.
No Tutorial Class or to be announced. Please check with the department offering this module.

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