课程与教学活动 - Teaching

 


          诚邀积极有为的学生加入我的团队!

          如果你对我的研究领域大学生实践项目充满好奇心和探究欲,寻找软件研发的乐趣,愿意全面提升个人专业能力,希望成功推进你的研究生学业、毕业设计或大学生实践活动,请联系我。

 

目前承担的各类课程


课程类别 课程名称 内容描述 课程时间

硕博研究生课程

(全英语)

Web挖掘技术

(Web Mining Technology)

     介绍万维网挖掘技术的最新发展和研究热点,对Web结构挖掘、Web内容挖掘和Web日志挖掘三个主要方向的技术、算法和应用,以及相关的衍生技术进行较深入的研讨。

    具体内容包括:万维网概述及Web数据分析;Web结构挖掘与信息检索;万维网内容挖掘;万维网使用记录挖掘;万维网挖掘算法性能评估技术和工具;万维网异常模式挖掘;Web挖掘技术的挑战与发展研讨。

春季学期

每周2学时

硕博研究生

核心课程

(全英语)

数据挖掘与数据仓库

(2016年校教学改革成果三等奖,研究生核心课程)

     课程介绍数据仓库系统和数据挖掘的概念和技术以及技术的实际应用。学生将学习数据仓库建模和系统结构设计的系列方法和海量数据管理,掌握基于数据仓库的数据分析和OLAP技术,以及这些技术在智能决策中的应用,从而帮助学生能初步应用数据仓库和OLAP技术解决实际问题。

     课程学习将学生引入数据挖掘技术领域,使他们理解该领域的问题空间。学生通过示例分析掌握基本数据挖掘技术,并能分析该领域的问题,提出初步的解决方案。

秋季学期

每周3学时

本科生课程 数据库原理与设计

(2016年校教学改革成果二等奖, 专业核心课程)

     本课程是计算机科学与技术、软件工程以及信息类相关专业的一门专业技术基础必修课。

    内容包括现实世界数据抽象,基本数据模型,数据库系统的结构和组成,关系数据库理论,数据库设计过程。课程侧重深入地阐述关系数据库理论及规范化理论,数据库的设计,操作语言,操作优化,并发控制,数据库安全及完整性控制等。使学生掌握数据库的基本理论、数据库的组织和结构,数据库系统的设计和开发方法,了解当前数据库的最新技术及最新发展。实验教学着重有关数据库应用系统的开发方法和基本技术。

    通过课程学习,学生理解并掌握数据库系统关键技术,具有开发基于数据库的信息系统应用的基本能力。

按不同专业

每周授课3学时+实验2学时

交大-利兹学院课程 Databases

Module summary:      Databases are a common component of many computer systems, storing and retrieving data about the state of a system. This module covers the principles of the design, architecture, implementation of database systems and the role of database management systems. In order to understand the design of database system an understanding of relational theory is required as well as the tools and techniques for decomposing systems and modelling them in an appropriate manner.This module introduces the tools for manipulating data in databases and design principles that ensure data security and integrity.

Objectives:     This module provides a foundation in the design and implementation of databases with an emphases on relational database systems.

Learning outcomes:      On successful completion of this module a student will have demonstrated the ability to: - describe the purpose and architecture of database management systems. - use appropriate tools to manipulate database systems. - design and implement a database using appropriate tools. - apply relational modelling techniques to real world situations. - apply normalisation and explain the advantages and disadvantages of normalisation. - describe the ethical, legal and security related issues concerning the implementation and administration of databases and their management systems.

Spring semester

3h/week, 10 weeks

 

正在指导/已结束的大学生实践项目

 

国创项目与SRTP项目 重点实验室大学生开发实践项目

2016-2017,基于Node.js+MongoDB构建校园生活指南系统

 

2016-2017,基于语音识别技术的电子密码锁的设计与实现

2013-2014,基于android的语音识别系统

2016-2017,基于MySQL数据库的商品比价系统

2013-2014,JSP自定义标签的实现

2013-2014,JavaScript恶意代码欺诈的检测技术研究( 四川省级大学生实践项目)

2013-2014,多种万维网使用挖掘的应用

2012-2013,国创项目: 基于内容的垃圾网页检测系统设计与实现

 

 

 


         I am looking for motivated students to work with!
        If you share my research interests, enjoy doing research work with practical and useful applications, and like to be the member of the software projects serving the needs of many key areas, then please do not hesitate to contact me!

 

Current Courses

Course Level Course Description Course Schedule

PhD students and Postgraduates

 

Web Mining Technology

(in English)

  1. This course will introduce Web mining technology and investigate how they are being used for discovering new patterns and rules from massive Web information.
  2. The key topics include Web content mining, Web structure mining, Web usage mining and Web spam detection.
  3. Students will gain a comprehensive and clear view of the development and challenges of Web mining. They should understand how to apply Web mining techniques to solve problems in real-world applications.
  4. By the end of the class, students should be familiar with the latest research developments and issues on data mining and can analyze a problem by using the Web mining techniques introduced in the course.

Spring semester

2h. per week

Key course for PhD students and Postgraduates

Data Warehousing and Data Mining

(in English)

  1. This course will introduce concepts and techniques of data warehousing and data mining and to investigate how these techniques are being used in applications.
  2. Students will learn the methodologies of data warehouse modeling and architecture design, as well as the techniques on OLAP and Business Intelligence-driven decision making.
  3. Students will gain a comprehensive view of data mining issues and approaches in this course and will understand basic data mining skills based on cases study.
  4. By the end of this course, students will be able to analyze and resolve problems in this area, and will be able to develop applications in data warehousing, OLAP, and Data Mining.

Autumn semester

3h. per week

Undergraduates Principle and Design of Databases
  1. This course covers both the principles and design of database management systems. Topics include database modeling, conceptual and logical database design, relational database pattern, the query language - SQL, database security, and transaction management. The query optimization techniques, relational data theory, concurrency control, database recovery, system security, and database integrity are also investigated in detail in the course.
  2. By the end of the class, students should master the concepts and techniques of RDBMS and have some experience both with building Databases and interacting with them programmatically.

3h/4h per week in terms of majors

Course of SWJTU-Leeds Joint School Databases
v.s.

v.s.

 

Copyright © Yan Zhu. Last updated: February 2018