• 第一节 万维网（World Wide Web） • 第二节 HTML • 第三节 Frontpage • 第四节 交互网页的制作 • 第五节 ASP（动态服务主页） • 第六节 Web数据库 • 第七节 关于Web2.0

1.3计算机语言和程序设计 1.4管理信息系统与数据库 1.5计算机绘图与计算机辅助设计 1.6多媒体技术 1.7计算机病毒的认识、预防与解毒 前四节请结合教材自学完成,下面重点 介绍第七节

 软件工作量估算的特点  软件工作量估算困难的原因  估算的基本方法  功能点方法和COCOMO模型  估算技巧  过于乐观的估计  有原则的谈判

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

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

7.1 Learn what Big Data is and how it is changing the world of analytics 7.2 Understand the motivation for and business drivers of Big Data analytics 7.3 Become familiar with the wide range of enabling technologies for Big Data analytics 7.4 Learn about Hadoop, MapReduce, and NoSQL as they relate to Big Data analytics 7.5 Compare and contrast the complementary uses of data warehousing and Big Data technologies 7.6 Become familiar with select Big Data platforms and services 7.7 Understand the need for and appreciate the capabilities of stream analytics 7.8 Learn about the applications of stream analytics

8.1 Explore some of the emerging technologies that may impact analytics, business intelligence (BI), and decision support 8.2 Describe the emerging Internet of Things (IoT) phenomenon, potential applications, and the IoT ecosystem 8.3 Describe the current and future use of cloud computing in business analytics 8.4 Describe how geospatial and location-based analytics are assisting organizations 8.5 Describe the organizational impacts of analytics applications 8.6 List and describe the major ethical and legal issues of analytics implementation 8.7 Identify key characteristics of a successful data science professional

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

一、专业方向课程 1、资源再生与生物能源 2、自然资源资产评估 3、清洁生产与循环经济 二、专业选修课程 1、环境管理与法学 2、计算机在环境中的应用 3、课题设计与论文写作 4、专业英语 三、实践性教学环节 1、生产实习 2、课程设计-资源再生与生物能源 3、毕业实习 4、毕业论文（设计）

通过本节内容的学习，了解计算机硬件技术、软件技术是信息系统的技术基础；理解计算 机系统的功能；理解和识别主要常见的计算机硬件设备；掌握计算机软件的主要分类构成。 教学重点 计算机的系统观；计算机的硬件及软件构成。 教学难点 计算机的系统观