Computer Science Department
Courant Institute of Mathematical Sciences



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Lectures
Prerequisites
Textbook
References
Slides
Handouts
Course Structure
NYU ID
Collaboration
Open Door Policy

Data Mining


G22.3033-002 - Spring 2010




Announcements

General Information

Instructor

Teaching Assistants and Graders

Lectures

  • Location: CIWW 101
  • Time: Thursdays 5:00-6:50 PM

Prerequisites

  • Students enrolling in this class should have taken introductory courses in databases and fundamental algorithms. Knowledge or experience in data warehousing, working knowledge of a mainstream database system (e.g., Microsoft SQL Server, IBM DB2, Oracle 11g), and previous programming experience in at least one higher-level procedural or object-oriented language are a plus.

Textbook(s)

  • Jiawei Han, Micheline Kamber, Data Mining: Concepts and Techniques (Second Edition), Morgan Kaufmann, ISBN-10: 1-55860-901-6, ISBN-13: 978-1-55860-901-3, 2nd Edition (2006)
  • Scott Cameron, Microsoft SQL Server 2008 Analysis Services Step by Step, Microsoft Press, ISBN-10: 0-73562-620-0, ISBN-13: 978-0-73562-620-31 1st Edition (04/15/09)

References

Slides

  • The powerpoint slides presented in class will be available for convenient browsing on the Web. The slide sets will also be available in PDF form for convenient printing and review.

Handouts

  • Handouts may also be distributed in class and will, in some cases, be available in electronic form on the class Web site.

Course Structure

There will be one required lectures each week. Readings will be assigned at the end of each lecture. There will be assignments and projects throughout the course. The due date will be specified on each given assignment. Homework will be generally due right before class on the day the assignments are due. The due dates for the assignments will be announced when the assignments are assigned. The submission method (i.e. electronic submission, paper submissions, the format, etc.) will be specified in each assignment. Late homework will not be accepted without the instructor's prior permission (see syllabus for details). Extensions are available only in the case of dire emergencies.

There is a final exam in this class, which will be either in-class or take-home.

Each student will have access to an I5 account. Please check with the instructor for information concerning your I5 account.

A class mailing list has been setup to facilitate communication with the class pertaining to questions, assignments, grades, changes in requirements etc. The class Web page is http://www.nyu.edu/classes/jcf/g22.3033-002/. This page will have further links to pages with announcements, handouts, etc. Students are required to log in and check the page at least once a week to make sure they are up to date with any information pertaining to the course.

The Web site is the primary means of getting information outside of class. The mailing list will be used for urgent messages, such a updates and hints for the homeworks.

If you have any questions, issues that you want to discuss, or things that you would like to have clarified, please see the instructor as soon as possible.

The final grade for the course will be determined as follows:
  • Assignments 25%
  • Projects 35%
  • Attendance and class participation 10%
  • Final 30%
  • Extra credit will be granted periodically for particular clever or creative solutions.
To receive a passing grade, you must complete satisfactory work in every area. In other words, you must receive passing grades for your homework (cumulatively) and a passing grade on the final.

If you have any concerns about your grade or about the grading, please feel free to see the instructor.

NYU ID

In order to access the ITS Computer Labs and Clusters, you must have a valid NYU ID card. See how to obtain an NYU ID card if you do not already have one.

Collaboration

You are required to do the assignments and projects by yourself; collaborating with other students or copying their work will not be tolerated. Anyone found copying or using another persons work will be dealt with under NYU's procedures for cheating. The consequences range from receiving a failing grade for the assignment to expulsion.

Please consult the department's academic integrity policy for more details.

However, we do strongly encourage students to discuss the materials covered in class. It is also acceptable to help or receive help from other students concerning features of Windows, Linux, or the UNIX operating system, or any other application that you use. There is a fine line between discussion and cheating. If you feel uncertain about whether you are crossing the line feel free to discuss these issues with the instructor before you do so.

Open Door Policy

We would like the course to run smoothly and enjoyably. Feel free to let the instructor know what you find good and interesting about the course. Let the instructor know sooner about the reverse. See the instructor, leave him a note, or send him an email.


Jean-Claude Franchitti, <jcf (followed by @, then cs, then a dot, then nyu, then a dot, and then edu)>
Last modified: Thu. April 29 04:31:18 EDT 2010