RU ENG ECE 16:332:568
Software Engineering of Web Applications

PDF document of the lecture notes (software engineering book) is available here   PDF icon

Spring 2009

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http://www.ece.rutgers.edu/~marsic/Teaching/SEW/
Lecture Schedule (Syllabus)
Instructor:
Ivan Marsic
Office hours: Tuesday 1:00 - 3:00 p.m.
Room 711, CoRE Building
Phone: (732) 445-6399
URL: http://www.ece.rutgers.edu/~marsic/

Lectures:
Friday: 4, 5 (1:40 p.m. - 4:40 p.m.) in SEC-212
… Friday: 4, 5 (1:40 p.m. - 4:40 p.m.) in CoRE-538

Course Description:
This course is problem-driven. Given a realistic problem (something relevant to real world), we study methods and technologies that could be applied to arrive at a solution. Unlike 16:332:567, Software Engineering I, the emphasis of this course is not on software methodology. Rather, our main emphasis will be on learning web technologies and trying to solve some realistic problems. Generally, the course covers web services (SOA - service oriented architecture) and data mining (web search and forecasting based on historic data). The Web contains huge quantities of data that are dynamically changing. This fact raises the need for automatic processing with sophisticated techniques known as machine intelligence. The key component of the course is a hands-on, software development project: getting a working code will be our main objective.

Prerequisites:
None.
It is recommended but not required that the student has taken 16:332:567, Software Engineering I.

Textbooks:
Christopher M. Bishop: Pattern Recognition and Machine Learning, Springer, 2006.
ISBN-13:   978-0-387-31073-2
Book information is available at: http://www.springer.com/west/home/computer/computer+imaging?SGWID=4-149-22-134256227-0
Also see the book website: Pattern Recognition and Machine Learning

Online Materials: Course Lecture Notes

Grading:
Students will work in groups of 2. Each group will prepare one lecture and work on a software project.
Before each lecture a reading list is assigned and everybody (not only presenters) should read all the papers and prepare a list of critical questions about the material. The questions shall be asked during or after the presentation, and, if necessary, emailed to the presenter(s). The presenter(s) should post to their web site within a week from the presentation the following:

Course grading works as follows.
- Report writeup and presentation:   30%   (Group)
- Critical questions asked to others:   20%   (Individual)
- Software development project:     50%   (Group)

Late assignments will be levied a late penalty of 10% per day, up to 3 days late. After that, no credit will be given, unless the student has a written excuse from a physician.

Students with Special Needs:
The University policy states that:
"It is the student's responsibility to confirm with the course supervisor that all arrangements are in place well in advance of the scheduled date of the exam."

If the student fails to make arrangements before the exams, we may not be able to accomodate the last-moment requests.

See also: A Faculty Guide to Accommodating Students with Disabilities. For students, look at Section III.

Feedback:
I'd be very happy to receive suggestions on how to improve the quality of the course and fairness of the grading process. Email me your suggestions and concerns.
To submit your feedback anonymously, please consider RateMyProfessor.com.


Page Created: Nov 24, 1999      
Last Modified: Mon Jan 14 19:10:27 EST 2008

Maintained by: Ivan Marsic