College of science in zulfi majmaah university

Courses Description

This course is the first of a two-course sequence in which the students will develop a complete software system. The second stage will be carried out in CSI420. Students will work in groups of up to four students, each group will have a supervisor to guide them through the system development process using a specific methodology.

In this first part, each group must identify a problem domain, define the problem, identify and specify the requirements, document the current system, analyze it, propose alternative systems, and design a solution. The design must include the definitions of all the required system models, such as the data model and the functional model. At the end of the course, each group must submit a formal report documenting the complete process.
Lab:

Non.

1. 
   To introduce the
   

6. 
   Introduce
   

Non.

This course presents number of powerful software technologies that will enable the student to build systems to integrate Internet, web components, and remote databases. It presents the “client-side” and “server-side” of web programming. For the client side it presents a carefully paced introduction to using the popular JavaScript language and the closely related technologies of XHTML (Extensible Hypertext Mark-up Language), CSS (Cascading Style Sheets). Novices will find that the material in the JavaScript chapters presents a solid foundation for the deeper treatment of scripting. The third class concentrates on using technologies such as web servers, databases (integrated collections of data), PHP, ASP.NET, to build the server side of web-based applications.

Internet Surfing, Create email account, Search Engines - Web Page Development –HTML, XML - using inline, internal, and external CSS - writing JavaScript inline, internal, and external codes - writing server side application using PHP - writing server side application using ASP.NET - building server side, client side integrated database application (Mini Project).

1. 
   Introduce the web development objective
   
2. 
   And Introduce the Hyper Text Markup Language HTML (30%)
   

3. 
   Introduce the Extensible Markup Language (XML (
   
4. 
   And Explore the difference between HTML and XML (10%)
   
5. 
   Use the Cascading Style Sheets (CSS) to design any webpage (25%(
   
6. 
   Introduce the Client_Side Scripting language (JavaScript) and Working with Server_side script language - PHP (20%(
   
7. 
   Working with Server_side script language – ASP.NET (15%).
   

1. 
   Use HTML and CSS to design different WebPages
   
2. 
   Use scripting languages to add interactivity to the WebPages
   
3. 
   differentiate between the client and server side programming
   
4. 
   Design different WebPages with different styling
   
5. 
   Program the server using the PHP
   
6. 
   Use the java scripts to design efficient WebPages
   
7. 
   Identify the methodology of physical model.
   
8. 
   On completing this course, the students are expected to be able to:
   

• 
  Design a group project
  
• 
  Implement different techniques discussed in the lectures during the course
  

David R. Brooks, G., “An Introduction to HTML and JavaScript: For Scientists and Engineers” , Publication Date: July 5, 2007 | ISBN-10: 1846286565 | ISBN-13: 978-1846286568 | Edition: 2007.

• 
  Programming the World Wide Web, 6/E, Robert W. Sebesta, University of Colorado, Colorado, Springs, ISBN-10: 0132130815, ISBN-13: 9780132130813, Addison-Wesley, 2011
  
• 
  Perry, Schneider: New Perspectives on The Internet Course Technology, 6th Edition ISBN 1-4188-6071-9.
  

This course introduces the basic theories and methodologies of data mining process includes data selection and cleaning, machine learning techniques to ``learn" knowledge that is ``hidden" in data, and the reporting and visualization of the resulting knowledge. This course will cover these issues and will illustrate the whole process by examples of practical applications from the life sciences, computer science, and commerce. Several machine learning topics including classification, prediction, and clustering will be covered. Machine learning packages.

To teach the student popular data mining tools such as WEKA: Introduction to Bioinformatics (2 Weeks) - Decision tree Ensemble methods (2 Week) -Multilinear and logistic regression (2 Weeks) - Perceptron Models Unsupervised Learning methods (2 Weeks) - Clustering Nice interactive k-means demo (2 Weeks) - Predicting Networks Through Bayesian Inference (2 Weeks). Applications of Spectral methods (2 Weeks) . Introduction to minimum description length (MDL) principle Kernel PCA (2 Weeks).

1. 
   To provide the student with an understanding of the concepts of data
   
2. 
   warehousing and data mining
   
3. 
   To study the dimensional modeling technique for designing a data warehouse
   
4. 
   To study data warehouse architectures, OLAP and the project planning aspects
   
5. 
   in building a data warehouse
   
6. 
   To explain the knowledge discovery process
   
7. 
   To describe the data mining tasks and study their well-known techniques
   

1. 
   Knowledge and understanding
   
2. 
   To discuss the different issues related to data warehousing and data mining.
   
3. 
   To provide students with a clear understanding of the different data warehouse
   
4. 
   architectures and data mining techniques
   
5. 
   Cognitive skills (thinking and analysis).
   
6. 
   To explain the nature of the knowledge discovery process and its challenges
   
7. 
   To explain the different data mining tasks and their common real world applications.
   
8. 
   Communication skills (personal and academic).
   
9. 
   To discuss the different evaluation methods of data mining and data warehousing.
   
10. 
    Practical and subject specific skills (Transferable Skills).
    
11. 
    To explain the different data mining tasks and their common real world applications.
    
12. 
    To teach the student popular data mining tools such as WEKA
    

• 
  Vipin Kumar, Introduction to Data Mining, Addison-Wesley - 2006.
  

• 
  M.H. Dunham, Data Mining (Introductory and Advanced Topics), Prentice-Hall, 2002
  
• 
  Berry M.J.A. & Linoff, G.S., Mastering Data Mining, Wiley 2000.
  
• 
  
  

This course introduces to students the following topics: Brief history of programming languages - Formal grammars - BNF notation - Principles of modern programming languages: features, design and evaluation - Imperative versus declarative language styles - General-purpose language features, such as types, operators, expressions, subprograms, recursion, and object-orientation - Special purpose language features, such as support for graphical interface, concurrency, and non-determinism - Relationship between language design and implementation.

Operational semantics, Assignment and basic control flow, Scope and variable binding, Simple types, Type safety, Shared-memory concurrency (threads, locks, transactions, memory-consistency models)

1. 
   Understand the concepts of programming languages by discussing the design issues of the various languages constructs.
   
2. 
   Examining the design choices for these constructs in some of the most common languages and critically comparing design alternatives.
   
3. 
   To provide the students with the tools necessary for the critical evaluation of existing and future programming languages.
   
4. 
   To prepare the student for the study of compiler design.
   
5. 
   It talks about many historical languages such as PASCAL, Ada, C, C++, Java, C# and others.
   

1. 
   Knowledge and understanding
   
2. 
   Understand the fundamental programming constructs.
   
3. 
   Understand and write searching and sorting techniques.
   
4. 
   Understand a typical C-like program environment.
   
5. 
   Cognitive skills (thinking and analysis).
   
6. 
   Be able to understand and analysis any problem and derive its solution.
   
7. 
   Be able to develop algorithms.
   
8. 
   Communication skills (personal and academic).
   
9. 
   Be able to work as a team
   
10. 
    Practical and subject specific skills (Transferable Skills).
    
11. 
    Be able to write C-like programs including searching and sorting techniques.
    

Robert W. Sebesta , Concepts of Programming languages, Addison-Wesley edition 7, 2006.

1. 
   David A. Watt, Programming Language Design Concepts, Wiley (May 31, 2004).