CS 412: Introduction to Data Mining
Provide a comprehensive overview of the fundamental concepts and techniques of data mining.
Classes: Tue, Thu 11:00 am – 12:15 am
Location: 1404 Siebel Center for Computer Science
Instructors: Arindam Banerjee, email@example.com
Ruby Tahboub, firstname.lastname@example.org
● Kowshika Sarker, email@example.com
● Rohan Deb:
● Sayar Ghosh Roy:
● Kowshika Sarker:
● Hyunsik Yoo:
Schedule (Tentative, subject to mild adjustments)
Coursework and Grading
▪ Project proposal: 15%
▪ Mid-term report: 35%
▪ Final report: 50%
❑ Following cutoffs represent what will likely be used to generate letter grades:
A+ >= 98% A >=94% & < 98% A- >=90% & < 94%
B+ >= 85% & < 90% B >=80% & < 85% B- >=77% & < 80%
C+ >= 74% & < 77% C >=70% & < 74% C- >=67% & <70%
D >= 60%& <67% F < 60%
❑ The above cutoffs are tentative and may be adjusted slightly; if there is any adjustment to the above cutoffs, we will NOT curve down your letter grades
❑ However, there will be no general curve-fitting in assigning the final grades
Required: Jiawei Han, Jian Pei, and Hanghang Tong, Data Mining: Concepts and Techniques
(4rd ed), Morgan Kaufmann, 2023
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to request appropriate accommodations. This should be done in the first two weeks of classes.
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