- Instructor:
- Ivan Marsic
Office hours: Monday 3:00 - 5:00 p.m.
Room 711, CoRE Building
Phone: (732) 445-6399
URL:
http://www.caip.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
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
Elliotte Rusty Harold, W. Scott Means:
XML in a Nutshell, Third Edition,
O'Reilly Media, Inc., 2004.
ISBN-10: 0-596-00764-7
Book information is available at:
http://www.oreilly.com/catalog/xmlnut3/
Michael Mahemoff:
Ajax Design Patterns,
O'Reilly Media, Inc., 2006.
ISBN-10: 0-596-10180-5
Book information is available at:
http://www.oreilly.com/catalog/ajaxdp/
- 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:
- Presentation slides, PowerPoint file
- A report summarizing the presented materials (10 - 20 pages), MS
Word or PDF file
- The list of critical questions and answers, attached at the end
of the report
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.