6.1 Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics 6.2 Understand the basic concepts of analytical decision modeling 6.3 Understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support 6.4 Describe how spreadsheets can be used for analytical modeling and solutions 6.5 Explain the basic concepts of optimization and when to use them 6.6 Describe how to structure a linear programming model 6.7 Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking 6.8 Understand the concepts and applications of different types of simulation 6.9 Understand potential applications of discrete event simulation

项目一 物流统计工作 项目二 物流调查技能与数据分析 项目三 物流市场供需统计分析 项目四 物流仓储统计分析 项目五 物流运输统计分析 项目六 物流配送统计分析 项目七 海关统计分析

OpenMP介绍 并行编程模式 并行域操作 工作共享结构

5.1 Describe text mining and understand the need for text mining 5.2 Differentiate among text analytics, text mining, and data mining 5.3 Understand the different application areas for text mining 5.4 Know the process of carrying out a text mining project 5.5 Appreciate the different methods to introduce structure to text-based data 5.6 Describe sentiment analysis 5.7 Develop familiarity with popular applications of sentiment analysis 5.8 Learn the common methods for sentiment analysis 5.9 Become familiar with speech analytics as it relates to sentiment analysis

4.1 Define data mining as an enabling technology for business analytics 4.2 Understand the objectives and benefits of data mining 4.3 Become familiar with the wide range of applications of data mining 4.4 Learn the standardized data mining processes 4.5 Learn different methods and algorithms of data mining 4.6 Build awareness of the existing data mining software tools 4.7 Understand the privacy issues, pitfalls, and myths of data mining

3.1 Understand the basic definitions and concepts of data warehousing 3.2 Understand data warehousing architectures 3.3 Describe the processes used in developing and managing data warehouses 3.4 Explain data warehousing operations 3.5 Explain the role of data warehouses in decision support

2.1 Understand the nature of data as it relates to business intelligence (BI) and analytics 2.2 Learn the methods used to make real-world data analytics ready 2.3 Describe statistical modeling and its relationship to business analytics 2.4 Learn about descriptive and inferential statistics 2.5 Define business reporting, and understand its historical evolution

1.1 Understand the need for computerized support of managerial decision making 1.2 Recognize the evolution of such computerized support to the current state—analytics/data science 1.3 Describe the business intelligence (BI) methodology and concepts 1.4 Understand the various types of analytics, and see selected applications 1.5 Understand the analytics ecosystem to identify various key players and career opportunities

1982年沈阳药学院药学系毕业,1984年获中国医科大学硕士学位, 1990年获北卡罗来那大学博土学位。1991-1995年在北卡罗来纳大学 和拜耳集团制药部从事博士后研究工作。1995年起任上海医科大学教 授,现为教育部长江学者奖励计划特聘教授、复旦大学药理研究中心 主任、巛 Molecular pain》等国内外刊物编委。 回国后在《Ce1l》等SCI刊物发表论文50余篇,研究结果揭示了 蛋白激酶在药物耐受成瘾中的关键作用和调节阿片类药物作用的新机 制,发现G蛋白偶联受体调控基因表达的表观遗传学新途径

第9章程序设计的一些编程技巧 9.1表处理程序设计 9.2代码转换程序 9.3算术运算 9.4数值分析