希望通过商业分析或培养商业分析能力以实现组织转型、职场成长的专业人员，可以通过学习本课程获得最大的收益，包括但不限于：
刘其章博士，1994年毕业于中国科技大学数学系计算数学专业，1997年获新加坡国立大 学数学博士学位。在加入新国大商学院之前，刘其章博士先后任职于研究所，软件公司和 新加坡理工学院，为新加坡航空、SMRT、新加坡国防部、新加坡图书馆、深圳航空和海南 航空等设计和开发智能管理系统，具有丰富的AI理论和实践经验。刘其章博士也多次获 得新加坡国立大学校级和学院级优秀教师奖，先后为多家中国的银行、保险公司和医疗 机构等提供大数据和人工智能方面的培训。
在瞬息万变而复杂的商业环境里，数据已经成为公司最重要的资产之一，而数据分析能力可以帮助组织机构充分利用数据来获取行业洞察，从而做出明智的决策。为了构建并实施富有成效的商业战略，您首先要确定组织机构，乃至整个行业在分析技术方面的主要挑战。正因为如此，对于希望在市场内抓住战略先机、取得竞争优势的专业人员而言，能够深入了解分析技术，无疑会帮助您在此过程中先拔头筹。
本课程将从商业预测的预测模型到因果分析的来龙去脉，再到数据集的隐私与安全，学员将接触到大数据应用程序、人工智能（AI）技术、真实案例研究，同时洞察分析工具的优劣以便借助其提升组织机构的灵活性并基于数据驱动的决策机制。
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学员只要顺利完成本课程，即可获颁新加坡国立大学商学院出具并认证的结业证书。
成功完成课程后，经过认证的数字证书将以您注册课程时使用的姓名通过电子邮件发送给您。 所有证书图片仅用于说明目的，新加坡国立大学商学院可能会酌情更改。 注：这一在线证书课程不授予新加坡国立大学的学分或学位。
立刻报名
Associate Professor Keppo teaches risk management and analytics courses, and directs analytics executive education programmes at NUS Business School. He is also Research Director of the Institute of Operations Research and Analytics at NUS. Previously, he taught at the University of Michigan.
He has several publications in the top-tier journals such as Journal of Economic Theory, Review of Economic Studies, Management Science, Operations Research, and Journal of Business on topics such as investment analysis, banking regulation, learning, and strategic incentives. His research has been featured also in numerous business and popular publications, including The Wall Street Journal and Fortune.
Associate Professor Keppo’s research has been supported by several Asian, European, and US agencies such as the National Science Foundation. He serves on the editorial boards of Management Science, Mathematics of Operations Research, Journal of Risk, Production and Operations Management, and Journal of Energy Markets. He has consulted several start-ups, Fortune 100 companies, and financial institutions.
Prasanta is an Adjunct Assistant Professor with the Department of Analytics and Operations (NUS Business School). He holds a PhD in Information Systems from the Department of Information Systems and Analytics, National University of Singapore, where he studied computational social science with a special focus on predictive and inferential methods in large social networks.
His current research agenda aims at understanding the role of big data in emerging social and business applications like digital marketing, micro-finance, healthcare, and urban systems. He actively collaborates and consults with leading industry partners from around the world, and regularly presents his research in major computer science, information systems, and marketing conferences worldwide.
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