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BISY90016Level 1 · 基础12.5 学分

Predictive Analytics

University of Melbourne

12.5
学分 Credits
L9
等级 Level
学期 Semester
Parkville
校区 Campus
课程描述 Description

Predicting key business variables has become increasingly important, as it drives both objective decision-making and improved profitability within organisations. This subject covers the main methods used to predict business variables, based on historical data. These include traditional regression, time series analysis, forecasting models, survival analysis, data mining, support vector machines and sentiment analysis. Throughout the subject, the focus will be on understanding how these methods are applied in various business problems, and identifying which predictive approach is the most appropriate to use, given a specific context. The importance of benchmarking different methodologies, as well as the use of prediction in decision-making frameworks, will also be emphasised.

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查看 Handbook 原文https://handbook.unimelb.edu.au/subjects/bisy90016
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📌 课程信息来源于 Melbourne University Handbook,选课建议为 AI 生成仅供参考。请以官方 Handbook 为准。
数据更新时间:2026 年 2 月 | WhiteMirror 不对信息准确性承担责任

BISY90016 · Predictive Analytics | 墨大专区 | WhiteMirror